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// Copyright (c) the JPEG XL Project Authors. All rights reserved.
//
// Use of this source code is governed by a BSD-style
// license that can be found in the LICENSE file.
#include "lib/jxl/dec_noise.h"
#include <cstdint>
#include <cstdlib>
#include <utility>
#undef HWY_TARGET_INCLUDE
#define HWY_TARGET_INCLUDE "lib/jxl/dec_noise.cc"
#include <hwy/foreach_target.h>
#include <hwy/highway.h>
#include "lib/jxl/base/compiler_specific.h"
#include "lib/jxl/base/rect.h"
#include "lib/jxl/frame_dimensions.h"
#include "lib/jxl/image.h"
#include "lib/jxl/xorshift128plus-inl.h"
HWY_BEFORE_NAMESPACE();
namespace jxl {
namespace HWY_NAMESPACE {
// These templates are not found via ADL.
using hwy::HWY_NAMESPACE::Or;
using hwy::HWY_NAMESPACE::ShiftRight;
using hwy::HWY_NAMESPACE::Vec;
using D = HWY_CAPPED(float, kBlockDim);
using DI = hwy::HWY_NAMESPACE::Rebind<int, D>;
using DI8 = hwy::HWY_NAMESPACE::Repartition<uint8_t, D>;
// Converts one vector's worth of random bits to floats in [1, 2).
// NOTE: as the convolution kernel sums to 0, it doesn't matter if inputs are in
// [0, 1) or in [1, 2).
void BitsToFloat(const uint32_t* JXL_RESTRICT random_bits,
float* JXL_RESTRICT floats) {
const HWY_FULL(float) df;
const HWY_FULL(uint32_t) du;
const auto bits = Load(du, random_bits);
// 1.0 + 23 random mantissa bits = [1, 2)
const auto rand12 = BitCast(df, Or(ShiftRight<9>(bits), Set(du, 0x3F800000)));
Store(rand12, df, floats);
}
void RandomImage(Xorshift128Plus* rng, const Rect& rect,
ImageF* JXL_RESTRICT noise) {
const size_t xsize = rect.xsize();
const size_t ysize = rect.ysize();
// May exceed the vector size, hence we have two loops over x below.
constexpr size_t kFloatsPerBatch =
Xorshift128Plus::N * sizeof(uint64_t) / sizeof(float);
HWY_ALIGN uint64_t batch[Xorshift128Plus::N] = {};
const HWY_FULL(float) df;
const size_t N = Lanes(df);
for (size_t y = 0; y < ysize; ++y) {
float* JXL_RESTRICT row = rect.Row(noise, y);
size_t x = 0;
// Only entire batches (avoids exceeding the image padding).
for (; x + kFloatsPerBatch < xsize; x += kFloatsPerBatch) {
rng->Fill(batch);
for (size_t i = 0; i < kFloatsPerBatch; i += Lanes(df)) {
BitsToFloat(reinterpret_cast<const uint32_t*>(batch) + i, row + x + i);
}
}
// Any remaining pixels, rounded up to vectors (safe due to padding).
rng->Fill(batch);
size_t batch_pos = 0; // < kFloatsPerBatch
for (; x < xsize; x += N) {
BitsToFloat(reinterpret_cast<const uint32_t*>(batch) + batch_pos,
row + x);
batch_pos += N;
}
}
}
void Random3Planes(size_t visible_frame_index, size_t nonvisible_frame_index,
size_t x0, size_t y0, const std::pair<ImageF*, Rect>& plane0,
const std::pair<ImageF*, Rect>& plane1,
const std::pair<ImageF*, Rect>& plane2) {
HWY_ALIGN Xorshift128Plus rng(visible_frame_index, nonvisible_frame_index, x0,
y0);
RandomImage(&rng, plane0.second, plane0.first);
RandomImage(&rng, plane1.second, plane1.first);
RandomImage(&rng, plane2.second, plane2.first);
}
// NOLINTNEXTLINE(google-readability-namespace-comments)
} // namespace HWY_NAMESPACE
} // namespace jxl
HWY_AFTER_NAMESPACE();
#if HWY_ONCE
namespace jxl {
namespace {
HWY_EXPORT(Random3Planes);
} // namespace
void PrepareNoiseInput(const PassesDecoderState& dec_state,
const FrameDimensions& frame_dim,
const FrameHeader& frame_header, size_t group_index,
size_t thread) {
size_t group_dim = frame_dim.group_dim;
const size_t gx = group_index % frame_dim.xsize_groups;
const size_t gy = group_index / frame_dim.xsize_groups;
RenderPipelineInput input =
dec_state.render_pipeline->GetInputBuffers(group_index, thread);
size_t noise_c_start =
3 + frame_header.nonserialized_metadata->m.num_extra_channels;
// When the color channels are downsampled, we need to generate more noise
// input for the current group than just the group dimensions.
std::pair<ImageF*, Rect> rects[3];
for (size_t iy = 0; iy < frame_header.upsampling; iy++) {
for (size_t ix = 0; ix < frame_header.upsampling; ix++) {
for (size_t c = 0; c < 3; c++) {
auto r = input.GetBuffer(noise_c_start + c);
rects[c].first = r.first;
size_t x1 = r.second.x0() + r.second.xsize();
size_t y1 = r.second.y0() + r.second.ysize();
rects[c].second =
Rect(r.second.x0() + ix * group_dim, r.second.y0() + iy * group_dim,
group_dim, group_dim, x1, y1);
}
HWY_DYNAMIC_DISPATCH(Random3Planes)
(dec_state.visible_frame_index, dec_state.nonvisible_frame_index,
(gx * frame_header.upsampling + ix) * group_dim,
(gy * frame_header.upsampling + iy) * group_dim, rects[0], rects[1],
rects[2]);
}
}
}
void DecodeFloatParam(float precision, float* val, BitReader* br) {
const int absval_quant = br->ReadFixedBits<10>();
*val = absval_quant / precision;
}
Status DecodeNoise(BitReader* br, NoiseParams* noise_params) {
for (float& i : noise_params->lut) {
DecodeFloatParam(kNoisePrecision, &i, br);
}
return true;
}
} // namespace jxl
#endif // HWY_ONCE