diff options
Diffstat (limited to 'third_party/jpeg-xl/lib/jxl/render_pipeline/stage_write.cc')
| -rw-r--r-- | third_party/jpeg-xl/lib/jxl/render_pipeline/stage_write.cc | 601 |
1 files changed, 601 insertions, 0 deletions
diff --git a/third_party/jpeg-xl/lib/jxl/render_pipeline/stage_write.cc b/third_party/jpeg-xl/lib/jxl/render_pipeline/stage_write.cc new file mode 100644 index 0000000000..902fc33b7e --- /dev/null +++ b/third_party/jpeg-xl/lib/jxl/render_pipeline/stage_write.cc @@ -0,0 +1,601 @@ +// 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/render_pipeline/stage_write.h" + +#include "lib/jxl/alpha.h" +#include "lib/jxl/common.h" +#include "lib/jxl/dec_cache.h" +#include "lib/jxl/image_bundle.h" +#include "lib/jxl/sanitizers.h" + +#undef HWY_TARGET_INCLUDE +#define HWY_TARGET_INCLUDE "lib/jxl/render_pipeline/stage_write.cc" +#include <hwy/foreach_target.h> +#include <hwy/highway.h> + +HWY_BEFORE_NAMESPACE(); +namespace jxl { +namespace HWY_NAMESPACE { + +// These templates are not found via ADL. +using hwy::HWY_NAMESPACE::Clamp; +using hwy::HWY_NAMESPACE::Div; +using hwy::HWY_NAMESPACE::Max; +using hwy::HWY_NAMESPACE::Mul; +using hwy::HWY_NAMESPACE::NearestInt; +using hwy::HWY_NAMESPACE::Or; +using hwy::HWY_NAMESPACE::Rebind; +using hwy::HWY_NAMESPACE::ShiftLeftSame; +using hwy::HWY_NAMESPACE::ShiftRightSame; + +class WriteToOutputStage : public RenderPipelineStage { + public: + WriteToOutputStage(const ImageOutput& main_output, size_t width, + size_t height, bool has_alpha, bool unpremul_alpha, + size_t alpha_c, Orientation undo_orientation, + const std::vector<ImageOutput>& extra_output) + : RenderPipelineStage(RenderPipelineStage::Settings()), + width_(width), + height_(height), + main_(main_output), + num_color_(main_.num_channels_ < 3 ? 1 : 3), + want_alpha_(main_.num_channels_ == 2 || main_.num_channels_ == 4), + has_alpha_(has_alpha), + unpremul_alpha_(unpremul_alpha), + alpha_c_(alpha_c), + flip_x_(ShouldFlipX(undo_orientation)), + flip_y_(ShouldFlipY(undo_orientation)), + transpose_(ShouldTranspose(undo_orientation)), + opaque_alpha_(kMaxPixelsPerCall, 1.0f) { + for (size_t ec = 0; ec < extra_output.size(); ++ec) { + if (extra_output[ec].callback.IsPresent() || extra_output[ec].buffer) { + Output extra(extra_output[ec]); + extra.channel_index_ = 3 + ec; + extra_channels_.push_back(extra); + } + } + } + + WriteToOutputStage(const WriteToOutputStage&) = delete; + WriteToOutputStage& operator=(const WriteToOutputStage&) = delete; + WriteToOutputStage(WriteToOutputStage&&) = delete; + WriteToOutputStage& operator=(WriteToOutputStage&&) = delete; + + ~WriteToOutputStage() override { + if (main_.run_opaque_) { + main_.pixel_callback_.destroy(main_.run_opaque_); + } + for (auto& extra : extra_channels_) { + if (extra.run_opaque_) { + extra.pixel_callback_.destroy(extra.run_opaque_); + } + } + } + + void ProcessRow(const RowInfo& input_rows, const RowInfo& output_rows, + size_t xextra, size_t xsize, size_t xpos, size_t ypos, + size_t thread_id) const final { + JXL_DASSERT(xextra == 0); + JXL_DASSERT(main_.run_opaque_ || main_.buffer_); + if (ypos >= height_) return; + if (xpos >= width_) return; + if (flip_y_) { + ypos = height_ - 1u - ypos; + } + size_t limit = std::min(xsize, width_ - xpos); + for (size_t x0 = 0; x0 < limit; x0 += kMaxPixelsPerCall) { + size_t xstart = xpos + x0; + size_t len = std::min<size_t>(kMaxPixelsPerCall, limit - x0); + + const float* line_buffers[4]; + for (size_t c = 0; c < num_color_; c++) { + line_buffers[c] = GetInputRow(input_rows, c, 0) + x0; + } + if (has_alpha_) { + line_buffers[num_color_] = GetInputRow(input_rows, alpha_c_, 0) + x0; + } else { + // opaque_alpha_ is a way to set all values to 1.0f. + line_buffers[num_color_] = opaque_alpha_.data(); + } + if (has_alpha_ && want_alpha_ && unpremul_alpha_) { + UnpremulAlpha(thread_id, len, line_buffers); + } + OutputBuffers(main_, thread_id, ypos, xstart, len, line_buffers); + for (const auto& extra : extra_channels_) { + line_buffers[0] = GetInputRow(input_rows, extra.channel_index_, 0) + x0; + OutputBuffers(extra, thread_id, ypos, xstart, len, line_buffers); + } + } + } + + RenderPipelineChannelMode GetChannelMode(size_t c) const final { + if (c < num_color_ || (has_alpha_ && c == alpha_c_)) { + return RenderPipelineChannelMode::kInput; + } + for (const auto& extra : extra_channels_) { + if (c == extra.channel_index_) { + return RenderPipelineChannelMode::kInput; + } + } + return RenderPipelineChannelMode::kIgnored; + } + + const char* GetName() const override { return "WritePixelCB"; } + + private: + struct Output { + Output(const ImageOutput& image_out) + : pixel_callback_(image_out.callback), + buffer_(image_out.buffer), + buffer_size_(image_out.buffer_size), + stride_(image_out.stride), + num_channels_(image_out.format.num_channels), + swap_endianness_(SwapEndianness(image_out.format.endianness)), + data_type_(image_out.format.data_type), + bits_per_sample_(image_out.bits_per_sample) {} + + Status PrepareForThreads(size_t num_threads) { + if (pixel_callback_.IsPresent()) { + run_opaque_ = + pixel_callback_.Init(num_threads, /*num_pixels=*/kMaxPixelsPerCall); + JXL_RETURN_IF_ERROR(run_opaque_ != nullptr); + } else { + JXL_RETURN_IF_ERROR(buffer_ != nullptr); + } + return true; + } + + PixelCallback pixel_callback_; + void* run_opaque_ = nullptr; + void* buffer_ = nullptr; + size_t buffer_size_; + size_t stride_; + size_t num_channels_; + bool swap_endianness_; + JxlDataType data_type_; + size_t bits_per_sample_; + size_t channel_index_; // used for extra_channels + }; + + Status PrepareForThreads(size_t num_threads) override { + JXL_RETURN_IF_ERROR(main_.PrepareForThreads(num_threads)); + for (auto& extra : extra_channels_) { + JXL_RETURN_IF_ERROR(extra.PrepareForThreads(num_threads)); + } + temp_out_.resize(num_threads); + for (CacheAlignedUniquePtr& temp : temp_out_) { + temp = AllocateArray(sizeof(float) * kMaxPixelsPerCall * + main_.num_channels_); + } + if ((has_alpha_ && want_alpha_ && unpremul_alpha_) || flip_x_) { + temp_in_.resize(num_threads * main_.num_channels_); + for (CacheAlignedUniquePtr& temp : temp_in_) { + temp = AllocateArray(sizeof(float) * kMaxPixelsPerCall); + } + } + return true; + } + static bool ShouldFlipX(Orientation undo_orientation) { + return (undo_orientation == Orientation::kFlipHorizontal || + undo_orientation == Orientation::kRotate180 || + undo_orientation == Orientation::kRotate270 || + undo_orientation == Orientation::kAntiTranspose); + } + static bool ShouldFlipY(Orientation undo_orientation) { + return (undo_orientation == Orientation::kFlipVertical || + undo_orientation == Orientation::kRotate180 || + undo_orientation == Orientation::kRotate90 || + undo_orientation == Orientation::kAntiTranspose); + } + static bool ShouldTranspose(Orientation undo_orientation) { + return (undo_orientation == Orientation::kTranspose || + undo_orientation == Orientation::kRotate90 || + undo_orientation == Orientation::kRotate270 || + undo_orientation == Orientation::kAntiTranspose); + } + + void UnpremulAlpha(size_t thread_id, size_t len, + const float** line_buffers) const { + const HWY_FULL(float) d; + auto one = Set(d, 1.0f); + float* temp_in[4]; + for (size_t c = 0; c < main_.num_channels_; ++c) { + size_t tix = thread_id * main_.num_channels_ + c; + temp_in[c] = reinterpret_cast<float*>(temp_in_[tix].get()); + memcpy(temp_in[c], line_buffers[c], sizeof(float) * len); + } + auto small_alpha = Set(d, kSmallAlpha); + for (size_t ix = 0; ix < len; ix += Lanes(d)) { + auto alpha = LoadU(d, temp_in[num_color_] + ix); + auto mul = Div(one, Max(small_alpha, alpha)); + for (size_t c = 0; c < num_color_; ++c) { + auto val = LoadU(d, temp_in[c] + ix); + StoreU(Mul(val, mul), d, temp_in[c] + ix); + } + } + for (size_t c = 0; c < main_.num_channels_; ++c) { + line_buffers[c] = temp_in[c]; + } + } + + void OutputBuffers(const Output& out, size_t thread_id, size_t ypos, + size_t xstart, size_t len, const float* input[4]) const { + if (flip_x_) { + FlipX(out, thread_id, len, &xstart, input); + } + if (out.data_type_ == JXL_TYPE_UINT8) { + uint8_t* JXL_RESTRICT temp = + reinterpret_cast<uint8_t*>(temp_out_[thread_id].get()); + StoreUnsignedRow(out, input, len, temp); + WriteToOutput(out, thread_id, ypos, xstart, len, temp); + } else if (out.data_type_ == JXL_TYPE_UINT16 || + out.data_type_ == JXL_TYPE_FLOAT16) { + uint16_t* JXL_RESTRICT temp = + reinterpret_cast<uint16_t*>(temp_out_[thread_id].get()); + if (out.data_type_ == JXL_TYPE_UINT16) { + StoreUnsignedRow(out, input, len, temp); + } else { + StoreFloat16Row(out, input, len, temp); + } + if (out.swap_endianness_) { + const HWY_FULL(uint16_t) du; + size_t output_len = len * out.num_channels_; + for (size_t j = 0; j < output_len; j += Lanes(du)) { + auto v = LoadU(du, temp + j); + auto vswap = Or(ShiftRightSame(v, 8), ShiftLeftSame(v, 8)); + StoreU(vswap, du, temp + j); + } + } + WriteToOutput(out, thread_id, ypos, xstart, len, temp); + } else if (out.data_type_ == JXL_TYPE_FLOAT) { + float* JXL_RESTRICT temp = + reinterpret_cast<float*>(temp_out_[thread_id].get()); + StoreFloatRow(out, input, len, temp); + if (out.swap_endianness_) { + size_t output_len = len * out.num_channels_; + for (size_t j = 0; j < output_len; ++j) { + temp[j] = BSwapFloat(temp[j]); + } + } + WriteToOutput(out, thread_id, ypos, xstart, len, temp); + } + } + + void FlipX(const Output& out, size_t thread_id, size_t len, size_t* xstart, + const float** line_buffers) const { + float* temp_in[4]; + for (size_t c = 0; c < out.num_channels_; ++c) { + size_t tix = thread_id * main_.num_channels_ + c; + temp_in[c] = reinterpret_cast<float*>(temp_in_[tix].get()); + if (temp_in[c] != line_buffers[c]) { + memcpy(temp_in[c], line_buffers[c], sizeof(float) * len); + } + } + size_t last = (len - 1u); + size_t num = (len / 2); + for (size_t i = 0; i < num; ++i) { + for (size_t c = 0; c < out.num_channels_; ++c) { + std::swap(temp_in[c][i], temp_in[c][last - i]); + } + } + for (size_t c = 0; c < out.num_channels_; ++c) { + line_buffers[c] = temp_in[c]; + } + *xstart = width_ - *xstart - len; + } + + template <typename T> + void StoreUnsignedRow(const Output& out, const float* input[4], size_t len, + T* output) const { + const HWY_FULL(float) d; + auto zero = Zero(d); + auto one = Set(d, 1.0f); + auto mul = Set(d, (1u << (out.bits_per_sample_)) - 1); + const Rebind<T, decltype(d)> du; + const size_t padding = RoundUpTo(len, Lanes(d)) - len; + for (size_t c = 0; c < out.num_channels_; ++c) { + msan::UnpoisonMemory(input[c] + len, sizeof(input[c][0]) * padding); + } + if (out.num_channels_ == 1) { + for (size_t i = 0; i < len; i += Lanes(d)) { + auto v0 = Mul(Clamp(zero, LoadU(d, &input[0][i]), one), mul); + StoreU(DemoteTo(du, NearestInt(v0)), du, &output[i]); + } + } else if (out.num_channels_ == 2) { + for (size_t i = 0; i < len; i += Lanes(d)) { + auto v0 = Mul(Clamp(zero, LoadU(d, &input[0][i]), one), mul); + auto v1 = Mul(Clamp(zero, LoadU(d, &input[1][i]), one), mul); + StoreInterleaved2(DemoteTo(du, NearestInt(v0)), + DemoteTo(du, NearestInt(v1)), du, &output[2 * i]); + } + } else if (out.num_channels_ == 3) { + for (size_t i = 0; i < len; i += Lanes(d)) { + auto v0 = Mul(Clamp(zero, LoadU(d, &input[0][i]), one), mul); + auto v1 = Mul(Clamp(zero, LoadU(d, &input[1][i]), one), mul); + auto v2 = Mul(Clamp(zero, LoadU(d, &input[2][i]), one), mul); + StoreInterleaved3(DemoteTo(du, NearestInt(v0)), + DemoteTo(du, NearestInt(v1)), + DemoteTo(du, NearestInt(v2)), du, &output[3 * i]); + } + } else if (out.num_channels_ == 4) { + for (size_t i = 0; i < len; i += Lanes(d)) { + auto v0 = Mul(Clamp(zero, LoadU(d, &input[0][i]), one), mul); + auto v1 = Mul(Clamp(zero, LoadU(d, &input[1][i]), one), mul); + auto v2 = Mul(Clamp(zero, LoadU(d, &input[2][i]), one), mul); + auto v3 = Mul(Clamp(zero, LoadU(d, &input[3][i]), one), mul); + StoreInterleaved4(DemoteTo(du, NearestInt(v0)), + DemoteTo(du, NearestInt(v1)), + DemoteTo(du, NearestInt(v2)), + DemoteTo(du, NearestInt(v3)), du, &output[4 * i]); + } + } + msan::PoisonMemory(output + out.num_channels_ * len, + sizeof(output[0]) * out.num_channels_ * padding); + } + + void StoreFloat16Row(const Output& out, const float* input[4], size_t len, + uint16_t* output) const { + const HWY_FULL(float) d; + const Rebind<uint16_t, decltype(d)> du; + const Rebind<hwy::float16_t, decltype(d)> df16; + const size_t padding = RoundUpTo(len, Lanes(d)) - len; + for (size_t c = 0; c < out.num_channels_; ++c) { + msan::UnpoisonMemory(input[c] + len, sizeof(input[c][0]) * padding); + } + if (out.num_channels_ == 1) { + for (size_t i = 0; i < len; i += Lanes(d)) { + auto v0 = LoadU(d, &input[0][i]); + StoreU(BitCast(du, DemoteTo(df16, v0)), du, &output[i]); + } + } else if (out.num_channels_ == 2) { + for (size_t i = 0; i < len; i += Lanes(d)) { + auto v0 = LoadU(d, &input[0][i]); + auto v1 = LoadU(d, &input[1][i]); + StoreInterleaved2(BitCast(du, DemoteTo(df16, v0)), + BitCast(du, DemoteTo(df16, v1)), du, &output[2 * i]); + } + } else if (out.num_channels_ == 3) { + for (size_t i = 0; i < len; i += Lanes(d)) { + auto v0 = LoadU(d, &input[0][i]); + auto v1 = LoadU(d, &input[1][i]); + auto v2 = LoadU(d, &input[2][i]); + StoreInterleaved3(BitCast(du, DemoteTo(df16, v0)), + BitCast(du, DemoteTo(df16, v1)), + BitCast(du, DemoteTo(df16, v2)), du, &output[3 * i]); + } + } else if (out.num_channels_ == 4) { + for (size_t i = 0; i < len; i += Lanes(d)) { + auto v0 = LoadU(d, &input[0][i]); + auto v1 = LoadU(d, &input[1][i]); + auto v2 = LoadU(d, &input[2][i]); + auto v3 = LoadU(d, &input[3][i]); + StoreInterleaved4(BitCast(du, DemoteTo(df16, v0)), + BitCast(du, DemoteTo(df16, v1)), + BitCast(du, DemoteTo(df16, v2)), + BitCast(du, DemoteTo(df16, v3)), du, &output[4 * i]); + } + } + msan::PoisonMemory(output + out.num_channels_ * len, + sizeof(output[0]) * out.num_channels_ * padding); + } + + void StoreFloatRow(const Output& out, const float* input[4], size_t len, + float* output) const { + const HWY_FULL(float) d; + if (out.num_channels_ == 1) { + memcpy(output, input[0], len * sizeof(output[0])); + } else if (out.num_channels_ == 2) { + for (size_t i = 0; i < len; i += Lanes(d)) { + StoreInterleaved2(LoadU(d, &input[0][i]), LoadU(d, &input[1][i]), d, + &output[2 * i]); + } + } else if (out.num_channels_ == 3) { + for (size_t i = 0; i < len; i += Lanes(d)) { + StoreInterleaved3(LoadU(d, &input[0][i]), LoadU(d, &input[1][i]), + LoadU(d, &input[2][i]), d, &output[3 * i]); + } + } else { + for (size_t i = 0; i < len; i += Lanes(d)) { + StoreInterleaved4(LoadU(d, &input[0][i]), LoadU(d, &input[1][i]), + LoadU(d, &input[2][i]), LoadU(d, &input[3][i]), d, + &output[4 * i]); + } + } + } + + template <typename T> + void WriteToOutput(const Output& out, size_t thread_id, size_t ypos, + size_t xstart, size_t len, T* output) const { + if (transpose_) { + // TODO(szabadka) Buffer 8x8 chunks and transpose with SIMD. + if (out.run_opaque_) { + for (size_t i = 0, j = 0; i < len; ++i, j += out.num_channels_) { + out.pixel_callback_.run(out.run_opaque_, thread_id, ypos, xstart + i, + 1, output + j); + } + } else { + const size_t pixel_stride = out.num_channels_ * sizeof(T); + const size_t offset = xstart * out.stride_ + ypos * pixel_stride; + for (size_t i = 0, j = 0; i < len; ++i, j += out.num_channels_) { + const size_t ix = offset + i * out.stride_; + JXL_DASSERT(ix + pixel_stride <= out.buffer_size_); + memcpy(reinterpret_cast<uint8_t*>(out.buffer_) + ix, output + j, + pixel_stride); + } + } + } else { + if (out.run_opaque_) { + out.pixel_callback_.run(out.run_opaque_, thread_id, xstart, ypos, len, + output); + } else { + const size_t pixel_stride = out.num_channels_ * sizeof(T); + const size_t offset = ypos * out.stride_ + xstart * pixel_stride; + JXL_DASSERT(offset + len * pixel_stride <= out.buffer_size_); + memcpy(reinterpret_cast<uint8_t*>(out.buffer_) + offset, output, + len * pixel_stride); + } + } + } + + static constexpr size_t kMaxPixelsPerCall = 1024; + size_t width_; + size_t height_; + Output main_; // color + alpha + size_t num_color_; + bool want_alpha_; + bool has_alpha_; + bool unpremul_alpha_; + size_t alpha_c_; + bool flip_x_; + bool flip_y_; + bool transpose_; + std::vector<Output> extra_channels_; + std::vector<float> opaque_alpha_; + std::vector<CacheAlignedUniquePtr> temp_in_; + std::vector<CacheAlignedUniquePtr> temp_out_; +}; + +constexpr size_t WriteToOutputStage::kMaxPixelsPerCall; + +std::unique_ptr<RenderPipelineStage> GetWriteToOutputStage( + const ImageOutput& main_output, size_t width, size_t height, bool has_alpha, + bool unpremul_alpha, size_t alpha_c, Orientation undo_orientation, + std::vector<ImageOutput>& extra_output) { + return jxl::make_unique<WriteToOutputStage>( + main_output, width, height, has_alpha, unpremul_alpha, alpha_c, + undo_orientation, extra_output); +} + +// NOLINTNEXTLINE(google-readability-namespace-comments) +} // namespace HWY_NAMESPACE +} // namespace jxl +HWY_AFTER_NAMESPACE(); + +#if HWY_ONCE + +namespace jxl { + +HWY_EXPORT(GetWriteToOutputStage); + +namespace { +class WriteToImageBundleStage : public RenderPipelineStage { + public: + explicit WriteToImageBundleStage(ImageBundle* image_bundle, + ColorEncoding color_encoding) + : RenderPipelineStage(RenderPipelineStage::Settings()), + image_bundle_(image_bundle), + color_encoding_(std::move(color_encoding)) {} + + void SetInputSizes( + const std::vector<std::pair<size_t, size_t>>& input_sizes) override { +#if JXL_ENABLE_ASSERT + JXL_ASSERT(input_sizes.size() >= 3); + for (size_t c = 1; c < input_sizes.size(); c++) { + JXL_ASSERT(input_sizes[c].first == input_sizes[0].first); + JXL_ASSERT(input_sizes[c].second == input_sizes[0].second); + } +#endif + // TODO(eustas): what should we do in the case of "want only ECs"? + image_bundle_->SetFromImage( + Image3F(input_sizes[0].first, input_sizes[0].second), color_encoding_); + // TODO(veluca): consider not reallocating ECs if not needed. + image_bundle_->extra_channels().clear(); + for (size_t c = 3; c < input_sizes.size(); c++) { + image_bundle_->extra_channels().emplace_back(input_sizes[c].first, + input_sizes[c].second); + } + } + + void ProcessRow(const RowInfo& input_rows, const RowInfo& output_rows, + size_t xextra, size_t xsize, size_t xpos, size_t ypos, + size_t thread_id) const final { + for (size_t c = 0; c < 3; c++) { + memcpy(image_bundle_->color()->PlaneRow(c, ypos) + xpos - xextra, + GetInputRow(input_rows, c, 0) - xextra, + sizeof(float) * (xsize + 2 * xextra)); + } + for (size_t ec = 0; ec < image_bundle_->extra_channels().size(); ec++) { + JXL_ASSERT(image_bundle_->extra_channels()[ec].xsize() >= + xpos + xsize + xextra); + memcpy(image_bundle_->extra_channels()[ec].Row(ypos) + xpos - xextra, + GetInputRow(input_rows, 3 + ec, 0) - xextra, + sizeof(float) * (xsize + 2 * xextra)); + } + } + + RenderPipelineChannelMode GetChannelMode(size_t c) const final { + return RenderPipelineChannelMode::kInput; + } + + const char* GetName() const override { return "WriteIB"; } + + private: + ImageBundle* image_bundle_; + ColorEncoding color_encoding_; +}; + +class WriteToImage3FStage : public RenderPipelineStage { + public: + explicit WriteToImage3FStage(Image3F* image) + : RenderPipelineStage(RenderPipelineStage::Settings()), image_(image) {} + + void SetInputSizes( + const std::vector<std::pair<size_t, size_t>>& input_sizes) override { +#if JXL_ENABLE_ASSERT + JXL_ASSERT(input_sizes.size() >= 3); + for (size_t c = 1; c < 3; ++c) { + JXL_ASSERT(input_sizes[c].first == input_sizes[0].first); + JXL_ASSERT(input_sizes[c].second == input_sizes[0].second); + } +#endif + *image_ = Image3F(input_sizes[0].first, input_sizes[0].second); + } + + void ProcessRow(const RowInfo& input_rows, const RowInfo& output_rows, + size_t xextra, size_t xsize, size_t xpos, size_t ypos, + size_t thread_id) const final { + for (size_t c = 0; c < 3; c++) { + memcpy(image_->PlaneRow(c, ypos) + xpos - xextra, + GetInputRow(input_rows, c, 0) - xextra, + sizeof(float) * (xsize + 2 * xextra)); + } + } + + RenderPipelineChannelMode GetChannelMode(size_t c) const final { + return c < 3 ? RenderPipelineChannelMode::kInput + : RenderPipelineChannelMode::kIgnored; + } + + const char* GetName() const override { return "WriteI3F"; } + + private: + Image3F* image_; +}; + +} // namespace + +std::unique_ptr<RenderPipelineStage> GetWriteToImageBundleStage( + ImageBundle* image_bundle, ColorEncoding color_encoding) { + return jxl::make_unique<WriteToImageBundleStage>(image_bundle, + std::move(color_encoding)); +} + +std::unique_ptr<RenderPipelineStage> GetWriteToImage3FStage(Image3F* image) { + return jxl::make_unique<WriteToImage3FStage>(image); +} + +std::unique_ptr<RenderPipelineStage> GetWriteToOutputStage( + const ImageOutput& main_output, size_t width, size_t height, bool has_alpha, + bool unpremul_alpha, size_t alpha_c, Orientation undo_orientation, + std::vector<ImageOutput>& extra_output) { + return HWY_DYNAMIC_DISPATCH(GetWriteToOutputStage)( + main_output, width, height, has_alpha, unpremul_alpha, alpha_c, + undo_orientation, extra_output); +} + +} // namespace jxl + +#endif |