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// Copyright 2019 The libgav1 Authors
//
// 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.
#include "src/utils/entropy_decoder.h"
#include <cassert>
#include <cstring>
#include "src/utils/common.h"
#include "src/utils/compiler_attributes.h"
#include "src/utils/constants.h"
#include "src/utils/cpu.h"
#if defined(__ARM_NEON__) || defined(__aarch64__) || \
(defined(_MSC_VER) && defined(_M_ARM))
#define LIBGAV1_ENTROPY_DECODER_ENABLE_NEON 1
#else
#define LIBGAV1_ENTROPY_DECODER_ENABLE_NEON 0
#endif
#if LIBGAV1_ENTROPY_DECODER_ENABLE_NEON
#include <arm_neon.h>
#endif
#if defined(__SSE2__) || defined(LIBGAV1_X86_MSVC)
#define LIBGAV1_ENTROPY_DECODER_ENABLE_SSE2 1
#else
#define LIBGAV1_ENTROPY_DECODER_ENABLE_SSE2 0
#endif
#if LIBGAV1_ENTROPY_DECODER_ENABLE_SSE2
#include <emmintrin.h>
#endif
namespace libgav1 {
namespace {
constexpr uint32_t kReadBitMask = ~255;
constexpr int kCdfPrecision = 6;
constexpr int kMinimumProbabilityPerSymbol = 4;
// This function computes the "cur" variable as specified inside the do-while
// loop in Section 8.2.6 of the spec. This function is monotonically
// decreasing as the values of index increases (note that the |cdf| array is
// sorted in decreasing order).
uint32_t ScaleCdf(uint32_t values_in_range_shifted, const uint16_t* const cdf,
int index, int symbol_count) {
return ((values_in_range_shifted * (cdf[index] >> kCdfPrecision)) >> 1) +
(kMinimumProbabilityPerSymbol * (symbol_count - index));
}
void UpdateCdf(uint16_t* LIBGAV1_RESTRICT const cdf, const int symbol_count,
const int symbol) {
const uint16_t count = cdf[symbol_count];
// rate is computed in the spec as:
// 3 + ( cdf[N] > 15 ) + ( cdf[N] > 31 ) + Min(FloorLog2(N), 2)
// In this case cdf[N] is |count|.
// Min(FloorLog2(N), 2) is 1 for symbol_count == {2, 3} and 2 for all
// symbol_count > 3. So the equation becomes:
// 4 + (count > 15) + (count > 31) + (symbol_count > 3).
// Note that the largest value for count is 32 (it is not incremented beyond
// 32). So using that information:
// count >> 4 is 0 for count from 0 to 15.
// count >> 4 is 1 for count from 16 to 31.
// count >> 4 is 2 for count == 31.
// Now, the equation becomes:
// 4 + (count >> 4) + (symbol_count > 3).
// Since (count >> 4) can only be 0 or 1 or 2, the addition could be replaced
// with bitwise or:
// (4 | (count >> 4)) + (symbol_count > 3).
// but using addition will allow the compiler to eliminate an operation when
// symbol_count is known and this function is inlined.
const int rate = (count >> 4) + 4 + static_cast<int>(symbol_count > 3);
// Hints for further optimizations:
//
// 1. clang can vectorize this for loop with width 4, even though the loop
// contains an if-else statement. Therefore, it may be advantageous to use
// "i < symbol_count" as the loop condition when symbol_count is 8, 12, or 16
// (a multiple of 4 that's not too small).
//
// 2. The for loop can be rewritten in the following form, which would enable
// clang to vectorize the loop with width 8:
//
// const int rounding = (1 << rate) - 1;
// for (int i = 0; i < symbol_count - 1; ++i) {
// const uint16_t a = (i < symbol) ? kCdfMaxProbability : rounding;
// cdf[i] += static_cast<int16_t>(a - cdf[i]) >> rate;
// }
//
// The subtraction (a - cdf[i]) relies on the overflow semantics of unsigned
// integer arithmetic. The result of the unsigned subtraction is cast to a
// signed integer and right-shifted. This requires the right shift of a
// signed integer be an arithmetic shift, which is true for clang, gcc, and
// Visual C++.
assert(symbol_count - 1 > 0);
int i = 0;
do {
if (i < symbol) {
cdf[i] += (kCdfMaxProbability - cdf[i]) >> rate;
} else {
cdf[i] -= cdf[i] >> rate;
}
} while (++i < symbol_count - 1);
cdf[symbol_count] += static_cast<uint16_t>(count < 32);
}
// Define the UpdateCdfN functions. UpdateCdfN is a specialized implementation
// of UpdateCdf based on the fact that symbol_count == N. UpdateCdfN uses the
// SIMD instruction sets if available.
#if LIBGAV1_ENTROPY_DECODER_ENABLE_NEON
// The UpdateCdf() method contains the following for loop:
//
// for (int i = 0; i < symbol_count - 1; ++i) {
// if (i < symbol) {
// cdf[i] += (kCdfMaxProbability - cdf[i]) >> rate;
// } else {
// cdf[i] -= cdf[i] >> rate;
// }
// }
//
// It can be rewritten in the following two forms, which are amenable to SIMD
// implementations:
//
// const int rounding = (1 << rate) - 1;
// for (int i = 0; i < symbol_count - 1; ++i) {
// const uint16_t a = (i < symbol) ? kCdfMaxProbability : rounding;
// cdf[i] += static_cast<int16_t>(a - cdf[i]) >> rate;
// }
//
// or:
//
// const int rounding = (1 << rate) - 1;
// for (int i = 0; i < symbol_count - 1; ++i) {
// const uint16_t a = (i < symbol) ? (kCdfMaxProbability - rounding) : 0;
// cdf[i] -= static_cast<int16_t>(cdf[i] - a) >> rate;
// }
//
// The following ARM NEON implementations use a modified version of the first
// form, using the comparison mask and unsigned rollover to avoid the need to
// calculate rounding.
//
// The cdf array has symbol_count + 1 elements. The first symbol_count elements
// are the CDF. The last element is a count that is initialized to 0 and may
// grow up to 32. The for loop in UpdateCdf updates the CDF in the array. Since
// cdf[symbol_count - 1] is always 0, the for loop does not update
// cdf[symbol_count - 1]. However, it would be correct to have the for loop
// update cdf[symbol_count - 1] anyway: since symbol_count - 1 >= symbol, the
// for loop would take the else branch when i is symbol_count - 1:
// cdf[i] -= cdf[i] >> rate;
// Since cdf[symbol_count - 1] is 0, cdf[symbol_count - 1] would still be 0
// after the update. The ARM NEON implementations take advantage of this in the
// following two cases:
// 1. When symbol_count is 8 or 16, the vectorized code updates the first
// symbol_count elements in the array.
// 2. When symbol_count is 7, the vectorized code updates all the 8 elements in
// the cdf array. Since an invalid CDF value is written into cdf[7], the
// count in cdf[7] needs to be fixed up after the vectorized code.
void UpdateCdf5(uint16_t* LIBGAV1_RESTRICT const cdf, const int symbol) {
uint16x4_t cdf_vec = vld1_u16(cdf);
const uint16_t count = cdf[5];
const int rate = (count >> 4) + 5;
const uint16x4_t cdf_max_probability = vdup_n_u16(kCdfMaxProbability);
const uint16x4_t index = vcreate_u16(0x0003000200010000);
const uint16x4_t symbol_vec = vdup_n_u16(symbol);
const uint16x4_t mask = vcge_u16(index, symbol_vec);
// i < symbol: 32768, i >= symbol: 65535.
const uint16x4_t a = vorr_u16(mask, cdf_max_probability);
// i < symbol: 32768 - cdf, i >= symbol: 65535 - cdf.
const int16x4_t diff = vreinterpret_s16_u16(vsub_u16(a, cdf_vec));
// i < symbol: cdf - 0, i >= symbol: cdf - 65535.
const uint16x4_t cdf_offset = vsub_u16(cdf_vec, mask);
const int16x4_t negative_rate = vdup_n_s16(-rate);
// i < symbol: (32768 - cdf) >> rate, i >= symbol: (65535 (-1) - cdf) >> rate.
const uint16x4_t delta = vreinterpret_u16_s16(vshl_s16(diff, negative_rate));
// i < symbol: (cdf - 0) + ((32768 - cdf) >> rate).
// i >= symbol: (cdf - 65535) + ((65535 - cdf) >> rate).
cdf_vec = vadd_u16(cdf_offset, delta);
vst1_u16(cdf, cdf_vec);
cdf[5] = count + static_cast<uint16_t>(count < 32);
}
// This version works for |symbol_count| = 7, 8, or 9.
// See UpdateCdf5 for implementation details.
template <int symbol_count>
void UpdateCdf7To9(uint16_t* LIBGAV1_RESTRICT const cdf, const int symbol) {
static_assert(symbol_count >= 7 && symbol_count <= 9, "");
uint16x8_t cdf_vec = vld1q_u16(cdf);
const uint16_t count = cdf[symbol_count];
const int rate = (count >> 4) + 5;
const uint16x8_t cdf_max_probability = vdupq_n_u16(kCdfMaxProbability);
const uint16x8_t index = vcombine_u16(vcreate_u16(0x0003000200010000),
vcreate_u16(0x0007000600050004));
const uint16x8_t symbol_vec = vdupq_n_u16(symbol);
const uint16x8_t mask = vcgeq_u16(index, symbol_vec);
const uint16x8_t a = vorrq_u16(mask, cdf_max_probability);
const int16x8_t diff = vreinterpretq_s16_u16(vsubq_u16(a, cdf_vec));
const uint16x8_t cdf_offset = vsubq_u16(cdf_vec, mask);
const int16x8_t negative_rate = vdupq_n_s16(-rate);
const uint16x8_t delta =
vreinterpretq_u16_s16(vshlq_s16(diff, negative_rate));
cdf_vec = vaddq_u16(cdf_offset, delta);
vst1q_u16(cdf, cdf_vec);
cdf[symbol_count] = count + static_cast<uint16_t>(count < 32);
}
void UpdateCdf7(uint16_t* const cdf, const int symbol) {
UpdateCdf7To9<7>(cdf, symbol);
}
void UpdateCdf8(uint16_t* const cdf, const int symbol) {
UpdateCdf7To9<8>(cdf, symbol);
}
void UpdateCdf9(uint16_t* const cdf, const int symbol) {
UpdateCdf7To9<9>(cdf, symbol);
}
// See UpdateCdf5 for implementation details.
void UpdateCdf11(uint16_t* LIBGAV1_RESTRICT const cdf, const int symbol) {
uint16x8_t cdf_vec = vld1q_u16(cdf + 2);
const uint16_t count = cdf[11];
cdf[11] = count + static_cast<uint16_t>(count < 32);
const int rate = (count >> 4) + 5;
if (symbol > 1) {
cdf[0] += (kCdfMaxProbability - cdf[0]) >> rate;
cdf[1] += (kCdfMaxProbability - cdf[1]) >> rate;
const uint16x8_t cdf_max_probability = vdupq_n_u16(kCdfMaxProbability);
const uint16x8_t symbol_vec = vdupq_n_u16(symbol);
const int16x8_t negative_rate = vdupq_n_s16(-rate);
const uint16x8_t index = vcombine_u16(vcreate_u16(0x0005000400030002),
vcreate_u16(0x0009000800070006));
const uint16x8_t mask = vcgeq_u16(index, symbol_vec);
const uint16x8_t a = vorrq_u16(mask, cdf_max_probability);
const int16x8_t diff = vreinterpretq_s16_u16(vsubq_u16(a, cdf_vec));
const uint16x8_t cdf_offset = vsubq_u16(cdf_vec, mask);
const uint16x8_t delta =
vreinterpretq_u16_s16(vshlq_s16(diff, negative_rate));
cdf_vec = vaddq_u16(cdf_offset, delta);
vst1q_u16(cdf + 2, cdf_vec);
} else {
if (symbol != 0) {
cdf[0] += (kCdfMaxProbability - cdf[0]) >> rate;
cdf[1] -= cdf[1] >> rate;
} else {
cdf[0] -= cdf[0] >> rate;
cdf[1] -= cdf[1] >> rate;
}
const int16x8_t negative_rate = vdupq_n_s16(-rate);
const uint16x8_t delta = vshlq_u16(cdf_vec, negative_rate);
cdf_vec = vsubq_u16(cdf_vec, delta);
vst1q_u16(cdf + 2, cdf_vec);
}
}
// See UpdateCdf5 for implementation details.
void UpdateCdf13(uint16_t* LIBGAV1_RESTRICT const cdf, const int symbol) {
uint16x8_t cdf_vec0 = vld1q_u16(cdf);
uint16x8_t cdf_vec1 = vld1q_u16(cdf + 4);
const uint16_t count = cdf[13];
const int rate = (count >> 4) + 5;
const uint16x8_t cdf_max_probability = vdupq_n_u16(kCdfMaxProbability);
const uint16x8_t symbol_vec = vdupq_n_u16(symbol);
const int16x8_t negative_rate = vdupq_n_s16(-rate);
uint16x8_t index = vcombine_u16(vcreate_u16(0x0003000200010000),
vcreate_u16(0x0007000600050004));
uint16x8_t mask = vcgeq_u16(index, symbol_vec);
uint16x8_t a = vorrq_u16(mask, cdf_max_probability);
int16x8_t diff = vreinterpretq_s16_u16(vsubq_u16(a, cdf_vec0));
uint16x8_t cdf_offset = vsubq_u16(cdf_vec0, mask);
uint16x8_t delta = vreinterpretq_u16_s16(vshlq_s16(diff, negative_rate));
cdf_vec0 = vaddq_u16(cdf_offset, delta);
vst1q_u16(cdf, cdf_vec0);
index = vcombine_u16(vcreate_u16(0x0007000600050004),
vcreate_u16(0x000b000a00090008));
mask = vcgeq_u16(index, symbol_vec);
a = vorrq_u16(mask, cdf_max_probability);
diff = vreinterpretq_s16_u16(vsubq_u16(a, cdf_vec1));
cdf_offset = vsubq_u16(cdf_vec1, mask);
delta = vreinterpretq_u16_s16(vshlq_s16(diff, negative_rate));
cdf_vec1 = vaddq_u16(cdf_offset, delta);
vst1q_u16(cdf + 4, cdf_vec1);
cdf[13] = count + static_cast<uint16_t>(count < 32);
}
// See UpdateCdf5 for implementation details.
void UpdateCdf16(uint16_t* LIBGAV1_RESTRICT const cdf, const int symbol) {
uint16x8_t cdf_vec = vld1q_u16(cdf);
const uint16_t count = cdf[16];
const int rate = (count >> 4) + 5;
const uint16x8_t cdf_max_probability = vdupq_n_u16(kCdfMaxProbability);
const uint16x8_t symbol_vec = vdupq_n_u16(symbol);
const int16x8_t negative_rate = vdupq_n_s16(-rate);
uint16x8_t index = vcombine_u16(vcreate_u16(0x0003000200010000),
vcreate_u16(0x0007000600050004));
uint16x8_t mask = vcgeq_u16(index, symbol_vec);
uint16x8_t a = vorrq_u16(mask, cdf_max_probability);
int16x8_t diff = vreinterpretq_s16_u16(vsubq_u16(a, cdf_vec));
uint16x8_t cdf_offset = vsubq_u16(cdf_vec, mask);
uint16x8_t delta = vreinterpretq_u16_s16(vshlq_s16(diff, negative_rate));
cdf_vec = vaddq_u16(cdf_offset, delta);
vst1q_u16(cdf, cdf_vec);
cdf_vec = vld1q_u16(cdf + 8);
index = vcombine_u16(vcreate_u16(0x000b000a00090008),
vcreate_u16(0x000f000e000d000c));
mask = vcgeq_u16(index, symbol_vec);
a = vorrq_u16(mask, cdf_max_probability);
diff = vreinterpretq_s16_u16(vsubq_u16(a, cdf_vec));
cdf_offset = vsubq_u16(cdf_vec, mask);
delta = vreinterpretq_u16_s16(vshlq_s16(diff, negative_rate));
cdf_vec = vaddq_u16(cdf_offset, delta);
vst1q_u16(cdf + 8, cdf_vec);
cdf[16] = count + static_cast<uint16_t>(count < 32);
}
#else // !LIBGAV1_ENTROPY_DECODER_ENABLE_NEON
#if LIBGAV1_ENTROPY_DECODER_ENABLE_SSE2
inline __m128i LoadLo8(const void* a) {
return _mm_loadl_epi64(static_cast<const __m128i*>(a));
}
inline __m128i LoadUnaligned16(const void* a) {
return _mm_loadu_si128(static_cast<const __m128i*>(a));
}
inline void StoreLo8(void* a, const __m128i v) {
_mm_storel_epi64(static_cast<__m128i*>(a), v);
}
inline void StoreUnaligned16(void* a, const __m128i v) {
_mm_storeu_si128(static_cast<__m128i*>(a), v);
}
void UpdateCdf5(uint16_t* LIBGAV1_RESTRICT const cdf, const int symbol) {
__m128i cdf_vec = LoadLo8(cdf);
const uint16_t count = cdf[5];
const int rate = (count >> 4) + 5;
const __m128i cdf_max_probability =
_mm_shufflelo_epi16(_mm_cvtsi32_si128(kCdfMaxProbability), 0);
const __m128i index = _mm_set_epi32(0x0, 0x0, 0x00040003, 0x00020001);
const __m128i symbol_vec = _mm_shufflelo_epi16(_mm_cvtsi32_si128(symbol), 0);
// i >= symbol.
const __m128i mask = _mm_cmpgt_epi16(index, symbol_vec);
// i < symbol: 32768, i >= symbol: 65535.
const __m128i a = _mm_or_si128(mask, cdf_max_probability);
// i < symbol: 32768 - cdf, i >= symbol: 65535 - cdf.
const __m128i diff = _mm_sub_epi16(a, cdf_vec);
// i < symbol: cdf - 0, i >= symbol: cdf - 65535.
const __m128i cdf_offset = _mm_sub_epi16(cdf_vec, mask);
// i < symbol: (32768 - cdf) >> rate, i >= symbol: (65535 (-1) - cdf) >> rate.
const __m128i delta = _mm_sra_epi16(diff, _mm_cvtsi32_si128(rate));
// i < symbol: (cdf - 0) + ((32768 - cdf) >> rate).
// i >= symbol: (cdf - 65535) + ((65535 - cdf) >> rate).
cdf_vec = _mm_add_epi16(cdf_offset, delta);
StoreLo8(cdf, cdf_vec);
cdf[5] = count + static_cast<uint16_t>(count < 32);
}
// This version works for |symbol_count| = 7, 8, or 9.
// See UpdateCdf5 for implementation details.
template <int symbol_count>
void UpdateCdf7To9(uint16_t* LIBGAV1_RESTRICT const cdf, const int symbol) {
static_assert(symbol_count >= 7 && symbol_count <= 9, "");
__m128i cdf_vec = LoadUnaligned16(cdf);
const uint16_t count = cdf[symbol_count];
const int rate = (count >> 4) + 5;
const __m128i cdf_max_probability =
_mm_set1_epi16(static_cast<int16_t>(kCdfMaxProbability));
const __m128i index =
_mm_set_epi32(0x00080007, 0x00060005, 0x00040003, 0x00020001);
const __m128i symbol_vec = _mm_set1_epi16(static_cast<int16_t>(symbol));
const __m128i mask = _mm_cmpgt_epi16(index, symbol_vec);
const __m128i a = _mm_or_si128(mask, cdf_max_probability);
const __m128i diff = _mm_sub_epi16(a, cdf_vec);
const __m128i cdf_offset = _mm_sub_epi16(cdf_vec, mask);
const __m128i delta = _mm_sra_epi16(diff, _mm_cvtsi32_si128(rate));
cdf_vec = _mm_add_epi16(cdf_offset, delta);
StoreUnaligned16(cdf, cdf_vec);
cdf[symbol_count] = count + static_cast<uint16_t>(count < 32);
}
void UpdateCdf7(uint16_t* const cdf, const int symbol) {
UpdateCdf7To9<7>(cdf, symbol);
}
void UpdateCdf8(uint16_t* const cdf, const int symbol) {
UpdateCdf7To9<8>(cdf, symbol);
}
void UpdateCdf9(uint16_t* const cdf, const int symbol) {
UpdateCdf7To9<9>(cdf, symbol);
}
// See UpdateCdf5 for implementation details.
void UpdateCdf11(uint16_t* LIBGAV1_RESTRICT const cdf, const int symbol) {
__m128i cdf_vec = LoadUnaligned16(cdf + 2);
const uint16_t count = cdf[11];
cdf[11] = count + static_cast<uint16_t>(count < 32);
const int rate = (count >> 4) + 5;
if (symbol > 1) {
cdf[0] += (kCdfMaxProbability - cdf[0]) >> rate;
cdf[1] += (kCdfMaxProbability - cdf[1]) >> rate;
const __m128i cdf_max_probability =
_mm_set1_epi16(static_cast<int16_t>(kCdfMaxProbability));
const __m128i index =
_mm_set_epi32(0x000a0009, 0x00080007, 0x00060005, 0x00040003);
const __m128i symbol_vec = _mm_set1_epi16(static_cast<int16_t>(symbol));
const __m128i mask = _mm_cmpgt_epi16(index, symbol_vec);
const __m128i a = _mm_or_si128(mask, cdf_max_probability);
const __m128i diff = _mm_sub_epi16(a, cdf_vec);
const __m128i cdf_offset = _mm_sub_epi16(cdf_vec, mask);
const __m128i delta = _mm_sra_epi16(diff, _mm_cvtsi32_si128(rate));
cdf_vec = _mm_add_epi16(cdf_offset, delta);
StoreUnaligned16(cdf + 2, cdf_vec);
} else {
if (symbol != 0) {
cdf[0] += (kCdfMaxProbability - cdf[0]) >> rate;
cdf[1] -= cdf[1] >> rate;
} else {
cdf[0] -= cdf[0] >> rate;
cdf[1] -= cdf[1] >> rate;
}
const __m128i delta = _mm_sra_epi16(cdf_vec, _mm_cvtsi32_si128(rate));
cdf_vec = _mm_sub_epi16(cdf_vec, delta);
StoreUnaligned16(cdf + 2, cdf_vec);
}
}
// See UpdateCdf5 for implementation details.
void UpdateCdf13(uint16_t* LIBGAV1_RESTRICT const cdf, const int symbol) {
__m128i cdf_vec0 = LoadLo8(cdf);
__m128i cdf_vec1 = LoadUnaligned16(cdf + 4);
const uint16_t count = cdf[13];
const int rate = (count >> 4) + 5;
const __m128i cdf_max_probability =
_mm_set1_epi16(static_cast<int16_t>(kCdfMaxProbability));
const __m128i symbol_vec = _mm_set1_epi16(static_cast<int16_t>(symbol));
const __m128i index = _mm_set_epi32(0x0, 0x0, 0x00040003, 0x00020001);
const __m128i mask = _mm_cmpgt_epi16(index, symbol_vec);
const __m128i a = _mm_or_si128(mask, cdf_max_probability);
const __m128i diff = _mm_sub_epi16(a, cdf_vec0);
const __m128i cdf_offset = _mm_sub_epi16(cdf_vec0, mask);
const __m128i delta = _mm_sra_epi16(diff, _mm_cvtsi32_si128(rate));
cdf_vec0 = _mm_add_epi16(cdf_offset, delta);
StoreLo8(cdf, cdf_vec0);
const __m128i index1 =
_mm_set_epi32(0x000c000b, 0x000a0009, 0x00080007, 0x00060005);
const __m128i mask1 = _mm_cmpgt_epi16(index1, symbol_vec);
const __m128i a1 = _mm_or_si128(mask1, cdf_max_probability);
const __m128i diff1 = _mm_sub_epi16(a1, cdf_vec1);
const __m128i cdf_offset1 = _mm_sub_epi16(cdf_vec1, mask1);
const __m128i delta1 = _mm_sra_epi16(diff1, _mm_cvtsi32_si128(rate));
cdf_vec1 = _mm_add_epi16(cdf_offset1, delta1);
StoreUnaligned16(cdf + 4, cdf_vec1);
cdf[13] = count + static_cast<uint16_t>(count < 32);
}
void UpdateCdf16(uint16_t* LIBGAV1_RESTRICT const cdf, const int symbol) {
__m128i cdf_vec0 = LoadUnaligned16(cdf);
const uint16_t count = cdf[16];
const int rate = (count >> 4) + 5;
const __m128i cdf_max_probability =
_mm_set1_epi16(static_cast<int16_t>(kCdfMaxProbability));
const __m128i symbol_vec = _mm_set1_epi16(static_cast<int16_t>(symbol));
const __m128i index =
_mm_set_epi32(0x00080007, 0x00060005, 0x00040003, 0x00020001);
const __m128i mask = _mm_cmpgt_epi16(index, symbol_vec);
const __m128i a = _mm_or_si128(mask, cdf_max_probability);
const __m128i diff = _mm_sub_epi16(a, cdf_vec0);
const __m128i cdf_offset = _mm_sub_epi16(cdf_vec0, mask);
const __m128i delta = _mm_sra_epi16(diff, _mm_cvtsi32_si128(rate));
cdf_vec0 = _mm_add_epi16(cdf_offset, delta);
StoreUnaligned16(cdf, cdf_vec0);
__m128i cdf_vec1 = LoadUnaligned16(cdf + 8);
const __m128i index1 =
_mm_set_epi32(0x0010000f, 0x000e000d, 0x000c000b, 0x000a0009);
const __m128i mask1 = _mm_cmpgt_epi16(index1, symbol_vec);
const __m128i a1 = _mm_or_si128(mask1, cdf_max_probability);
const __m128i diff1 = _mm_sub_epi16(a1, cdf_vec1);
const __m128i cdf_offset1 = _mm_sub_epi16(cdf_vec1, mask1);
const __m128i delta1 = _mm_sra_epi16(diff1, _mm_cvtsi32_si128(rate));
cdf_vec1 = _mm_add_epi16(cdf_offset1, delta1);
StoreUnaligned16(cdf + 8, cdf_vec1);
cdf[16] = count + static_cast<uint16_t>(count < 32);
}
#else // !LIBGAV1_ENTROPY_DECODER_ENABLE_SSE2
void UpdateCdf5(uint16_t* const cdf, const int symbol) {
UpdateCdf(cdf, 5, symbol);
}
void UpdateCdf7(uint16_t* const cdf, const int symbol) {
UpdateCdf(cdf, 7, symbol);
}
void UpdateCdf8(uint16_t* const cdf, const int symbol) {
UpdateCdf(cdf, 8, symbol);
}
void UpdateCdf9(uint16_t* const cdf, const int symbol) {
UpdateCdf(cdf, 9, symbol);
}
void UpdateCdf11(uint16_t* const cdf, const int symbol) {
UpdateCdf(cdf, 11, symbol);
}
void UpdateCdf13(uint16_t* const cdf, const int symbol) {
UpdateCdf(cdf, 13, symbol);
}
void UpdateCdf16(uint16_t* const cdf, const int symbol) {
UpdateCdf(cdf, 16, symbol);
}
#endif // LIBGAV1_ENTROPY_DECODER_ENABLE_SSE2
#endif // LIBGAV1_ENTROPY_DECODER_ENABLE_NEON
inline EntropyDecoder::WindowSize HostToBigEndian(
const EntropyDecoder::WindowSize x) {
static_assert(sizeof(x) == 4 || sizeof(x) == 8, "");
#if defined(__GNUC__)
#if __BYTE_ORDER__ == __ORDER_LITTLE_ENDIAN__
return (sizeof(x) == 8) ? __builtin_bswap64(x) : __builtin_bswap32(x);
#else
return x;
#endif
#elif defined(_WIN32)
// Note Windows targets are assumed to be little endian.
return static_cast<EntropyDecoder::WindowSize>(
(sizeof(x) == 8) ? _byteswap_uint64(static_cast<unsigned __int64>(x))
: _byteswap_ulong(static_cast<unsigned long>(x)));
#else
#error Unknown compiler!
#endif // defined(__GNUC__)
}
} // namespace
#if !LIBGAV1_CXX17
constexpr int EntropyDecoder::kWindowSize; // static.
#endif
EntropyDecoder::EntropyDecoder(const uint8_t* data, size_t size,
bool allow_update_cdf)
: data_(data),
data_end_(data + size),
data_memcpy_end_((size >= sizeof(WindowSize))
? data + size - sizeof(WindowSize) + 1
: data),
allow_update_cdf_(allow_update_cdf),
values_in_range_(kCdfMaxProbability) {
if (data_ < data_memcpy_end_) {
// This is a simplified version of PopulateBits() which loads 8 extra bits
// and skips the unnecessary shifts of value and window_diff_.
WindowSize value;
memcpy(&value, data_, sizeof(value));
data_ += sizeof(value);
window_diff_ = HostToBigEndian(value) ^ -1;
// Note the initial value of bits_ is larger than kMaxCachedBits as it's
// used to restore the most significant 0 bit that would be present after
// PopulateBits() when we extract the first symbol value.
// As shown in Section 8.2.2 Initialization process for symbol decoder,
// which uses a fixed offset to read the symbol values, the most
// significant bit is always 0:
// The variable numBits is set equal to Min( sz * 8, 15).
// The variable buf is read using the f(numBits) parsing process.
// The variable paddedBuf is set equal to ( buf << (15 - numBits) ).
// The variable SymbolValue is set to ((1 << 15) - 1) ^ paddedBuf.
bits_ = kWindowSize - 15;
return;
}
window_diff_ = 0;
bits_ = -15;
PopulateBits();
}
// This is similar to the ReadSymbol() implementation but it is optimized based
// on the following facts:
// * The probability is fixed at half. So some multiplications can be replaced
// with bit operations.
// * Symbol count is fixed at 2.
int EntropyDecoder::ReadBit() {
const uint32_t curr =
((values_in_range_ & kReadBitMask) >> 1) + kMinimumProbabilityPerSymbol;
const auto symbol_value = static_cast<uint16_t>(window_diff_ >> bits_);
int bit = 1;
if (symbol_value >= curr) {
values_in_range_ -= curr;
window_diff_ -= static_cast<WindowSize>(curr) << bits_;
bit = 0;
} else {
values_in_range_ = curr;
}
NormalizeRange();
return bit;
}
int64_t EntropyDecoder::ReadLiteral(int num_bits) {
assert(num_bits <= 32);
assert(num_bits > 0);
uint32_t literal = 0;
int bit = num_bits - 1;
do {
// ARM can combine a shift operation with a constant number of bits with
// some other operations, such as the OR operation.
// Here is an ARM disassembly example:
// orr w1, w0, w1, lsl #1
// which left shifts register w1 by 1 bit and OR the shift result with
// register w0.
// The next 2 lines are equivalent to:
// literal |= static_cast<uint32_t>(ReadBit()) << bit;
literal <<= 1;
literal |= static_cast<uint32_t>(ReadBit());
} while (--bit >= 0);
return literal;
}
int EntropyDecoder::ReadSymbol(uint16_t* LIBGAV1_RESTRICT const cdf,
int symbol_count) {
const int symbol = ReadSymbolImpl(cdf, symbol_count);
if (allow_update_cdf_) {
UpdateCdf(cdf, symbol_count, symbol);
}
return symbol;
}
bool EntropyDecoder::ReadSymbol(uint16_t* LIBGAV1_RESTRICT cdf) {
assert(cdf[1] == 0);
const bool symbol = ReadSymbolImpl(cdf[0]) != 0;
if (allow_update_cdf_) {
const uint16_t count = cdf[2];
// rate is computed in the spec as:
// 3 + ( cdf[N] > 15 ) + ( cdf[N] > 31 ) + Min(FloorLog2(N), 2)
// In this case N is 2 and cdf[N] is |count|. So the equation becomes:
// 4 + (count > 15) + (count > 31)
// Note that the largest value for count is 32 (it is not incremented beyond
// 32). So using that information:
// count >> 4 is 0 for count from 0 to 15.
// count >> 4 is 1 for count from 16 to 31.
// count >> 4 is 2 for count == 32.
// Now, the equation becomes:
// 4 + (count >> 4).
// Since (count >> 4) can only be 0 or 1 or 2, the addition can be replaced
// with bitwise or. So the final equation is:
// 4 | (count >> 4).
const int rate = 4 | (count >> 4);
if (symbol) {
cdf[0] += (kCdfMaxProbability - cdf[0]) >> rate;
} else {
cdf[0] -= cdf[0] >> rate;
}
cdf[2] += static_cast<uint16_t>(count < 32);
}
return symbol;
}
bool EntropyDecoder::ReadSymbolWithoutCdfUpdate(uint16_t cdf) {
return ReadSymbolImpl(cdf) != 0;
}
template <int symbol_count>
int EntropyDecoder::ReadSymbol(uint16_t* LIBGAV1_RESTRICT const cdf) {
static_assert(symbol_count >= 3 && symbol_count <= 16, "");
if (symbol_count == 3 || symbol_count == 4) {
return ReadSymbol3Or4(cdf, symbol_count);
}
int symbol;
if (symbol_count == 8) {
symbol = ReadSymbolImpl8(cdf);
} else if (symbol_count <= 13) {
symbol = ReadSymbolImpl(cdf, symbol_count);
} else {
symbol = ReadSymbolImplBinarySearch(cdf, symbol_count);
}
if (allow_update_cdf_) {
if (symbol_count == 5) {
UpdateCdf5(cdf, symbol);
} else if (symbol_count == 7) {
UpdateCdf7(cdf, symbol);
} else if (symbol_count == 8) {
UpdateCdf8(cdf, symbol);
} else if (symbol_count == 9) {
UpdateCdf9(cdf, symbol);
} else if (symbol_count == 11) {
UpdateCdf11(cdf, symbol);
} else if (symbol_count == 13) {
UpdateCdf13(cdf, symbol);
} else if (symbol_count == 16) {
UpdateCdf16(cdf, symbol);
} else {
UpdateCdf(cdf, symbol_count, symbol);
}
}
return symbol;
}
int EntropyDecoder::ReadSymbolImpl(const uint16_t* LIBGAV1_RESTRICT const cdf,
int symbol_count) {
assert(cdf[symbol_count - 1] == 0);
--symbol_count;
uint32_t curr = values_in_range_;
int symbol = -1;
uint32_t prev;
const auto symbol_value = static_cast<uint16_t>(window_diff_ >> bits_);
uint32_t delta = kMinimumProbabilityPerSymbol * symbol_count;
// Search through the |cdf| array to determine where the scaled cdf value and
// |symbol_value| cross over.
do {
prev = curr;
curr = (((values_in_range_ >> 8) * (cdf[++symbol] >> kCdfPrecision)) >> 1) +
delta;
delta -= kMinimumProbabilityPerSymbol;
} while (symbol_value < curr);
values_in_range_ = prev - curr;
window_diff_ -= static_cast<WindowSize>(curr) << bits_;
NormalizeRange();
return symbol;
}
int EntropyDecoder::ReadSymbolImplBinarySearch(
const uint16_t* LIBGAV1_RESTRICT const cdf, int symbol_count) {
assert(cdf[symbol_count - 1] == 0);
assert(symbol_count > 1 && symbol_count <= 16);
--symbol_count;
const auto symbol_value = static_cast<uint16_t>(window_diff_ >> bits_);
// Search through the |cdf| array to determine where the scaled cdf value and
// |symbol_value| cross over. Since the CDFs are sorted, we can use binary
// search to do this. Let |symbol| be the index of the first |cdf| array
// entry whose scaled cdf value is less than or equal to |symbol_value|. The
// binary search maintains the invariant:
// low <= symbol <= high + 1
// and terminates when low == high + 1.
int low = 0;
int high = symbol_count - 1;
// The binary search maintains the invariants that |prev| is the scaled cdf
// value for low - 1 and |curr| is the scaled cdf value for high + 1. (By
// convention, the scaled cdf value for -1 is values_in_range_.) When the
// binary search terminates, |prev| is the scaled cdf value for symbol - 1
// and |curr| is the scaled cdf value for |symbol|.
uint32_t prev = values_in_range_;
uint32_t curr = 0;
const uint32_t values_in_range_shifted = values_in_range_ >> 8;
do {
const int mid = DivideBy2(low + high);
const uint32_t scaled_cdf =
ScaleCdf(values_in_range_shifted, cdf, mid, symbol_count);
if (symbol_value < scaled_cdf) {
low = mid + 1;
prev = scaled_cdf;
} else {
high = mid - 1;
curr = scaled_cdf;
}
} while (low <= high);
assert(low == high + 1);
// At this point, |low| is the symbol that has been decoded.
values_in_range_ = prev - curr;
window_diff_ -= static_cast<WindowSize>(curr) << bits_;
NormalizeRange();
return low;
}
int EntropyDecoder::ReadSymbolImpl(uint16_t cdf) {
const auto symbol_value = static_cast<uint16_t>(window_diff_ >> bits_);
const uint32_t curr =
(((values_in_range_ >> 8) * (cdf >> kCdfPrecision)) >> 1) +
kMinimumProbabilityPerSymbol;
const int symbol = static_cast<int>(symbol_value < curr);
if (symbol == 1) {
values_in_range_ = curr;
} else {
values_in_range_ -= curr;
window_diff_ -= static_cast<WindowSize>(curr) << bits_;
}
NormalizeRange();
return symbol;
}
// Equivalent to ReadSymbol(cdf, [3,4]), with the ReadSymbolImpl and UpdateCdf
// calls inlined.
int EntropyDecoder::ReadSymbol3Or4(uint16_t* LIBGAV1_RESTRICT const cdf,
const int symbol_count) {
assert(cdf[symbol_count - 1] == 0);
uint32_t curr = values_in_range_;
uint32_t prev;
const auto symbol_value = static_cast<uint16_t>(window_diff_ >> bits_);
uint32_t delta = kMinimumProbabilityPerSymbol * (symbol_count - 1);
const uint32_t values_in_range_shifted = values_in_range_ >> 8;
// Search through the |cdf| array to determine where the scaled cdf value and
// |symbol_value| cross over. If allow_update_cdf_ is true, update the |cdf|
// array.
//
// The original code is:
//
// int symbol = -1;
// do {
// prev = curr;
// curr =
// ((values_in_range_shifted * (cdf[++symbol] >> kCdfPrecision)) >> 1)
// + delta;
// delta -= kMinimumProbabilityPerSymbol;
// } while (symbol_value < curr);
// if (allow_update_cdf_) {
// UpdateCdf(cdf, [3,4], symbol);
// }
//
// The do-while loop is unrolled with three or four iterations, and the
// UpdateCdf call is inlined and merged into the iterations.
int symbol = 0;
// Iteration 0.
prev = curr;
curr =
((values_in_range_shifted * (cdf[symbol] >> kCdfPrecision)) >> 1) + delta;
if (symbol_value >= curr) {
// symbol == 0.
if (allow_update_cdf_) {
// Inlined version of UpdateCdf(cdf, [3,4], /*symbol=*/0).
const uint16_t count = cdf[symbol_count];
cdf[symbol_count] += static_cast<uint16_t>(count < 32);
const int rate = (count >> 4) + 4 + static_cast<int>(symbol_count == 4);
if (symbol_count == 4) {
#if LIBGAV1_ENTROPY_DECODER_ENABLE_NEON
// 1. On Motorola Moto G5 Plus (running 32-bit Android 8.1.0), the ARM
// NEON code is slower. Consider using the C version if __arm__ is
// defined.
// 2. The ARM NEON code (compiled for arm64) is slightly slower on
// Samsung Galaxy S8+ (SM-G955FD).
uint16x4_t cdf_vec = vld1_u16(cdf);
const int16x4_t negative_rate = vdup_n_s16(-rate);
const uint16x4_t delta = vshl_u16(cdf_vec, negative_rate);
cdf_vec = vsub_u16(cdf_vec, delta);
vst1_u16(cdf, cdf_vec);
#elif LIBGAV1_ENTROPY_DECODER_ENABLE_SSE2
__m128i cdf_vec = LoadLo8(cdf);
const __m128i delta = _mm_sra_epi16(cdf_vec, _mm_cvtsi32_si128(rate));
cdf_vec = _mm_sub_epi16(cdf_vec, delta);
StoreLo8(cdf, cdf_vec);
#else // !LIBGAV1_ENTROPY_DECODER_ENABLE_SSE2
cdf[0] -= cdf[0] >> rate;
cdf[1] -= cdf[1] >> rate;
cdf[2] -= cdf[2] >> rate;
#endif
} else { // symbol_count == 3.
cdf[0] -= cdf[0] >> rate;
cdf[1] -= cdf[1] >> rate;
}
}
goto found;
}
++symbol;
delta -= kMinimumProbabilityPerSymbol;
// Iteration 1.
prev = curr;
curr =
((values_in_range_shifted * (cdf[symbol] >> kCdfPrecision)) >> 1) + delta;
if (symbol_value >= curr) {
// symbol == 1.
if (allow_update_cdf_) {
// Inlined version of UpdateCdf(cdf, [3,4], /*symbol=*/1).
const uint16_t count = cdf[symbol_count];
cdf[symbol_count] += static_cast<uint16_t>(count < 32);
const int rate = (count >> 4) + 4 + static_cast<int>(symbol_count == 4);
cdf[0] += (kCdfMaxProbability - cdf[0]) >> rate;
cdf[1] -= cdf[1] >> rate;
if (symbol_count == 4) cdf[2] -= cdf[2] >> rate;
}
goto found;
}
++symbol;
if (symbol_count == 4) {
delta -= kMinimumProbabilityPerSymbol;
// Iteration 2.
prev = curr;
curr = ((values_in_range_shifted * (cdf[symbol] >> kCdfPrecision)) >> 1) +
delta;
if (symbol_value >= curr) {
// symbol == 2.
if (allow_update_cdf_) {
// Inlined version of UpdateCdf(cdf, 4, /*symbol=*/2).
const uint16_t count = cdf[4];
cdf[4] += static_cast<uint16_t>(count < 32);
const int rate = (count >> 4) + 5;
cdf[0] += (kCdfMaxProbability - cdf[0]) >> rate;
cdf[1] += (kCdfMaxProbability - cdf[1]) >> rate;
cdf[2] -= cdf[2] >> rate;
}
goto found;
}
++symbol;
}
// |delta| is 0 for the last iteration.
// Iteration 2 (symbol_count == 3) or 3 (symbol_count == 4).
prev = curr;
// Since cdf[symbol_count - 1] is 0 and |delta| is 0, |curr| is also 0.
curr = 0;
// symbol == [2,3].
if (allow_update_cdf_) {
// Inlined version of UpdateCdf(cdf, [3,4], /*symbol=*/[2,3]).
const uint16_t count = cdf[symbol_count];
cdf[symbol_count] += static_cast<uint16_t>(count < 32);
const int rate = (4 | (count >> 4)) + static_cast<int>(symbol_count == 4);
if (symbol_count == 4) {
#if LIBGAV1_ENTROPY_DECODER_ENABLE_NEON
// On Motorola Moto G5 Plus (running 32-bit Android 8.1.0), the ARM NEON
// code is a tiny bit slower. Consider using the C version if __arm__ is
// defined.
uint16x4_t cdf_vec = vld1_u16(cdf);
const uint16x4_t cdf_max_probability = vdup_n_u16(kCdfMaxProbability);
const int16x4_t diff =
vreinterpret_s16_u16(vsub_u16(cdf_max_probability, cdf_vec));
const int16x4_t negative_rate = vdup_n_s16(-rate);
const uint16x4_t delta =
vreinterpret_u16_s16(vshl_s16(diff, negative_rate));
cdf_vec = vadd_u16(cdf_vec, delta);
vst1_u16(cdf, cdf_vec);
cdf[3] = 0;
#elif LIBGAV1_ENTROPY_DECODER_ENABLE_SSE2
__m128i cdf_vec = LoadLo8(cdf);
const __m128i cdf_max_probability =
_mm_shufflelo_epi16(_mm_cvtsi32_si128(kCdfMaxProbability), 0);
const __m128i diff = _mm_sub_epi16(cdf_max_probability, cdf_vec);
const __m128i delta = _mm_sra_epi16(diff, _mm_cvtsi32_si128(rate));
cdf_vec = _mm_add_epi16(cdf_vec, delta);
StoreLo8(cdf, cdf_vec);
cdf[3] = 0;
#else // !LIBGAV1_ENTROPY_DECODER_ENABLE_SSE2
cdf[0] += (kCdfMaxProbability - cdf[0]) >> rate;
cdf[1] += (kCdfMaxProbability - cdf[1]) >> rate;
cdf[2] += (kCdfMaxProbability - cdf[2]) >> rate;
#endif
} else { // symbol_count == 3.
cdf[0] += (kCdfMaxProbability - cdf[0]) >> rate;
cdf[1] += (kCdfMaxProbability - cdf[1]) >> rate;
}
}
found:
// End of unrolled do-while loop.
values_in_range_ = prev - curr;
window_diff_ -= static_cast<WindowSize>(curr) << bits_;
NormalizeRange();
return symbol;
}
int EntropyDecoder::ReadSymbolImpl8(
const uint16_t* LIBGAV1_RESTRICT const cdf) {
assert(cdf[7] == 0);
uint32_t curr = values_in_range_;
uint32_t prev;
const auto symbol_value = static_cast<uint16_t>(window_diff_ >> bits_);
uint32_t delta = kMinimumProbabilityPerSymbol * 7;
// Search through the |cdf| array to determine where the scaled cdf value and
// |symbol_value| cross over.
//
// The original code is:
//
// int symbol = -1;
// do {
// prev = curr;
// curr =
// (((values_in_range_ >> 8) * (cdf[++symbol] >> kCdfPrecision)) >> 1)
// + delta;
// delta -= kMinimumProbabilityPerSymbol;
// } while (symbol_value < curr);
//
// The do-while loop is unrolled with eight iterations.
int symbol = 0;
#define READ_SYMBOL_ITERATION \
prev = curr; \
curr = (((values_in_range_ >> 8) * (cdf[symbol] >> kCdfPrecision)) >> 1) + \
delta; \
if (symbol_value >= curr) goto found; \
++symbol; \
delta -= kMinimumProbabilityPerSymbol
READ_SYMBOL_ITERATION; // Iteration 0.
READ_SYMBOL_ITERATION; // Iteration 1.
READ_SYMBOL_ITERATION; // Iteration 2.
READ_SYMBOL_ITERATION; // Iteration 3.
READ_SYMBOL_ITERATION; // Iteration 4.
READ_SYMBOL_ITERATION; // Iteration 5.
// The last two iterations can be simplified, so they don't use the
// READ_SYMBOL_ITERATION macro.
#undef READ_SYMBOL_ITERATION
// Iteration 6.
prev = curr;
curr =
(((values_in_range_ >> 8) * (cdf[symbol] >> kCdfPrecision)) >> 1) + delta;
if (symbol_value >= curr) goto found; // symbol == 6.
++symbol;
// |delta| is 0 for the last iteration.
// Iteration 7.
prev = curr;
// Since cdf[7] is 0 and |delta| is 0, |curr| is also 0.
curr = 0;
// symbol == 7.
found:
// End of unrolled do-while loop.
values_in_range_ = prev - curr;
window_diff_ -= static_cast<WindowSize>(curr) << bits_;
NormalizeRange();
return symbol;
}
void EntropyDecoder::PopulateBits() {
constexpr int kMaxCachedBits = kWindowSize - 16;
#if defined(__aarch64__)
// Fast path: read eight bytes and add the first six bytes to window_diff_.
// This fast path makes the following assumptions.
// 1. We assume that unaligned load of uint64_t is fast.
// 2. When there are enough bytes in data_, the for loop below reads 6 or 7
// bytes depending on the value of bits_. This fast path always reads 6
// bytes, which results in more calls to PopulateBits(). We assume that
// making more calls to a faster PopulateBits() is overall a win.
// NOTE: Although this fast path could also be used on x86_64, it hurts
// performance (measured on Lenovo ThinkStation P920 running Linux). (The
// reason is still unknown.) Therefore this fast path is only used on arm64.
static_assert(kWindowSize == 64, "");
if (data_ < data_memcpy_end_) {
uint64_t value;
// arm64 supports unaligned loads, so this memcpy call is compiled to a
// single ldr instruction.
memcpy(&value, data_, sizeof(value));
data_ += kMaxCachedBits >> 3;
value = HostToBigEndian(value) ^ -1;
value >>= kWindowSize - kMaxCachedBits;
window_diff_ = value | (window_diff_ << kMaxCachedBits);
bits_ += kMaxCachedBits;
return;
}
#endif
const uint8_t* data = data_;
int bits = bits_;
WindowSize window_diff = window_diff_;
int count = kWindowSize - 9 - (bits + 15);
// The fast path above, if compiled, would cause clang 8.0.7 to vectorize
// this loop. Since -15 <= bits_ <= -1, this loop has at most 6 or 7
// iterations when WindowSize is 64 bits. So it is not profitable to
// vectorize this loop. Note that clang 8.0.7 does not vectorize this loop if
// the fast path above is not compiled.
#ifdef __clang__
#pragma clang loop vectorize(disable) interleave(disable)
#endif
for (; count >= 0 && data < data_end_; count -= 8) {
const uint8_t value = *data++ ^ -1;
window_diff = static_cast<WindowSize>(value) | (window_diff << 8);
bits += 8;
}
assert(bits <= kMaxCachedBits);
if (data == data_end_) {
// Shift in some 1s. This is equivalent to providing fake 0 data bits.
window_diff = ((window_diff + 1) << (kMaxCachedBits - bits)) - 1;
bits = kMaxCachedBits;
}
data_ = data;
bits_ = bits;
window_diff_ = window_diff;
}
void EntropyDecoder::NormalizeRange() {
const int bits_used = 15 ^ FloorLog2(values_in_range_);
bits_ -= bits_used;
values_in_range_ <<= bits_used;
if (bits_ < 0) PopulateBits();
}
// Explicit instantiations.
template int EntropyDecoder::ReadSymbol<3>(uint16_t* cdf);
template int EntropyDecoder::ReadSymbol<4>(uint16_t* cdf);
template int EntropyDecoder::ReadSymbol<5>(uint16_t* cdf);
template int EntropyDecoder::ReadSymbol<6>(uint16_t* cdf);
template int EntropyDecoder::ReadSymbol<7>(uint16_t* cdf);
template int EntropyDecoder::ReadSymbol<8>(uint16_t* cdf);
template int EntropyDecoder::ReadSymbol<9>(uint16_t* cdf);
template int EntropyDecoder::ReadSymbol<10>(uint16_t* cdf);
template int EntropyDecoder::ReadSymbol<11>(uint16_t* cdf);
template int EntropyDecoder::ReadSymbol<12>(uint16_t* cdf);
template int EntropyDecoder::ReadSymbol<13>(uint16_t* cdf);
template int EntropyDecoder::ReadSymbol<14>(uint16_t* cdf);
template int EntropyDecoder::ReadSymbol<16>(uint16_t* cdf);
} // namespace libgav1