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82f20cdcc0
https://github.com/ARM-software/astc-encoder/releases/tag/4.5.0 https://github.com/ARM-software/astc-encoder/releases/tag/4.6.0 https://github.com/ARM-software/astc-encoder/releases/tag/4.7.0
1457 lines
48 KiB
C++
1457 lines
48 KiB
C++
// SPDX-License-Identifier: Apache-2.0
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// ----------------------------------------------------------------------------
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// Copyright 2011-2024 Arm Limited
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//
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// Licensed under the Apache License, Version 2.0 (the "License"); you may not
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// use this file except in compliance with the License. You may obtain a copy
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// of the License at:
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
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// WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
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// License for the specific language governing permissions and limitations
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// under the License.
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// ----------------------------------------------------------------------------
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#if !defined(ASTCENC_DECOMPRESS_ONLY)
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/**
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* @brief Functions to compress a symbolic block.
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*/
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#include "astcenc_internal.h"
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#include "astcenc_diagnostic_trace.h"
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#include <cassert>
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/**
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* @brief Merge two planes of endpoints into a single vector.
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*
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* @param ep_plane1 The endpoints for plane 1.
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* @param ep_plane2 The endpoints for plane 2.
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* @param component_plane2 The color component for plane 2.
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* @param[out] result The merged output.
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*/
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static void merge_endpoints(
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const endpoints& ep_plane1,
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const endpoints& ep_plane2,
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unsigned int component_plane2,
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endpoints& result
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) {
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unsigned int partition_count = ep_plane1.partition_count;
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assert(partition_count == 1);
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vmask4 sep_mask = vint4::lane_id() == vint4(component_plane2);
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result.partition_count = partition_count;
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result.endpt0[0] = select(ep_plane1.endpt0[0], ep_plane2.endpt0[0], sep_mask);
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result.endpt1[0] = select(ep_plane1.endpt1[0], ep_plane2.endpt1[0], sep_mask);
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}
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/**
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* @brief Attempt to improve weights given a chosen configuration.
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*
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* Given a fixed weight grid decimation and weight value quantization, iterate over all weights (per
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* partition and per plane) and attempt to improve image quality by moving each weight up by one or
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* down by one quantization step.
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*
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* This is a specialized function which only supports operating on undecimated weight grids,
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* therefore primarily improving the performance of 4x4 and 5x5 blocks where grid decimation
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* is needed less often.
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*
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* @param decode_mode The decode mode (LDR, HDR).
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* @param bsd The block size information.
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* @param blk The image block color data to compress.
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* @param[out] scb The symbolic compressed block output.
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*/
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static bool realign_weights_undecimated(
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astcenc_profile decode_mode,
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const block_size_descriptor& bsd,
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const image_block& blk,
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symbolic_compressed_block& scb
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) {
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// Get the partition descriptor
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unsigned int partition_count = scb.partition_count;
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const auto& pi = bsd.get_partition_info(partition_count, scb.partition_index);
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// Get the quantization table
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const block_mode& bm = bsd.get_block_mode(scb.block_mode);
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unsigned int weight_quant_level = bm.quant_mode;
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const quant_and_transfer_table& qat = quant_and_xfer_tables[weight_quant_level];
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unsigned int max_plane = bm.is_dual_plane;
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int plane2_component = scb.plane2_component;
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vmask4 plane_mask = vint4::lane_id() == vint4(plane2_component);
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// Decode the color endpoints
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bool rgb_hdr;
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bool alpha_hdr;
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vint4 endpnt0[BLOCK_MAX_PARTITIONS];
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vint4 endpnt1[BLOCK_MAX_PARTITIONS];
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vfloat4 endpnt0f[BLOCK_MAX_PARTITIONS];
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vfloat4 offset[BLOCK_MAX_PARTITIONS];
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promise(partition_count > 0);
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for (unsigned int pa_idx = 0; pa_idx < partition_count; pa_idx++)
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{
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unpack_color_endpoints(decode_mode,
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scb.color_formats[pa_idx],
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scb.color_values[pa_idx],
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rgb_hdr, alpha_hdr,
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endpnt0[pa_idx],
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endpnt1[pa_idx]);
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}
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uint8_t* dec_weights_uquant = scb.weights;
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bool adjustments = false;
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// For each plane and partition ...
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for (unsigned int pl_idx = 0; pl_idx <= max_plane; pl_idx++)
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{
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for (unsigned int pa_idx = 0; pa_idx < partition_count; pa_idx++)
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{
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// Compute the endpoint delta for all components in current plane
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vint4 epd = endpnt1[pa_idx] - endpnt0[pa_idx];
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epd = select(epd, vint4::zero(), plane_mask);
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endpnt0f[pa_idx] = int_to_float(endpnt0[pa_idx]);
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offset[pa_idx] = int_to_float(epd) * (1.0f / 64.0f);
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}
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// For each weight compute previous, current, and next errors
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promise(bsd.texel_count > 0);
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for (unsigned int texel = 0; texel < bsd.texel_count; texel++)
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{
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int uqw = dec_weights_uquant[texel];
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uint32_t prev_and_next = qat.prev_next_values[uqw];
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int uqw_down = prev_and_next & 0xFF;
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int uqw_up = (prev_and_next >> 8) & 0xFF;
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// Interpolate the colors to create the diffs
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float weight_base = static_cast<float>(uqw);
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float weight_down = static_cast<float>(uqw_down - uqw);
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float weight_up = static_cast<float>(uqw_up - uqw);
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unsigned int partition = pi.partition_of_texel[texel];
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vfloat4 color_offset = offset[partition];
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vfloat4 color_base = endpnt0f[partition];
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vfloat4 color = color_base + color_offset * weight_base;
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vfloat4 orig_color = blk.texel(texel);
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vfloat4 error_weight = blk.channel_weight;
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vfloat4 color_diff = color - orig_color;
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vfloat4 color_diff_down = color_diff + color_offset * weight_down;
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vfloat4 color_diff_up = color_diff + color_offset * weight_up;
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float error_base = dot_s(color_diff * color_diff, error_weight);
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float error_down = dot_s(color_diff_down * color_diff_down, error_weight);
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float error_up = dot_s(color_diff_up * color_diff_up, error_weight);
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// Check if the prev or next error is better, and if so use it
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if ((error_up < error_base) && (error_up < error_down) && (uqw < 64))
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{
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dec_weights_uquant[texel] = static_cast<uint8_t>(uqw_up);
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adjustments = true;
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}
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else if ((error_down < error_base) && (uqw > 0))
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{
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dec_weights_uquant[texel] = static_cast<uint8_t>(uqw_down);
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adjustments = true;
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}
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}
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// Prepare iteration for plane 2
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dec_weights_uquant += WEIGHTS_PLANE2_OFFSET;
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plane_mask = ~plane_mask;
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}
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return adjustments;
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}
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/**
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* @brief Attempt to improve weights given a chosen configuration.
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*
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* Given a fixed weight grid decimation and weight value quantization, iterate over all weights (per
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* partition and per plane) and attempt to improve image quality by moving each weight up by one or
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* down by one quantization step.
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*
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* @param decode_mode The decode mode (LDR, HDR).
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* @param bsd The block size information.
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* @param blk The image block color data to compress.
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* @param[out] scb The symbolic compressed block output.
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*/
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static bool realign_weights_decimated(
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astcenc_profile decode_mode,
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const block_size_descriptor& bsd,
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const image_block& blk,
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symbolic_compressed_block& scb
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) {
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// Get the partition descriptor
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unsigned int partition_count = scb.partition_count;
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const auto& pi = bsd.get_partition_info(partition_count, scb.partition_index);
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// Get the quantization table
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const block_mode& bm = bsd.get_block_mode(scb.block_mode);
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unsigned int weight_quant_level = bm.quant_mode;
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const quant_and_transfer_table& qat = quant_and_xfer_tables[weight_quant_level];
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// Get the decimation table
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const decimation_info& di = bsd.get_decimation_info(bm.decimation_mode);
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unsigned int weight_count = di.weight_count;
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assert(weight_count != bsd.texel_count);
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unsigned int max_plane = bm.is_dual_plane;
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int plane2_component = scb.plane2_component;
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vmask4 plane_mask = vint4::lane_id() == vint4(plane2_component);
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// Decode the color endpoints
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bool rgb_hdr;
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bool alpha_hdr;
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vint4 endpnt0[BLOCK_MAX_PARTITIONS];
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vint4 endpnt1[BLOCK_MAX_PARTITIONS];
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vfloat4 endpnt0f[BLOCK_MAX_PARTITIONS];
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vfloat4 offset[BLOCK_MAX_PARTITIONS];
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promise(partition_count > 0);
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promise(weight_count > 0);
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for (unsigned int pa_idx = 0; pa_idx < partition_count; pa_idx++)
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{
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unpack_color_endpoints(decode_mode,
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scb.color_formats[pa_idx],
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scb.color_values[pa_idx],
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rgb_hdr, alpha_hdr,
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endpnt0[pa_idx],
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endpnt1[pa_idx]);
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}
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uint8_t* dec_weights_uquant = scb.weights;
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bool adjustments = false;
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// For each plane and partition ...
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for (unsigned int pl_idx = 0; pl_idx <= max_plane; pl_idx++)
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{
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for (unsigned int pa_idx = 0; pa_idx < partition_count; pa_idx++)
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{
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// Compute the endpoint delta for all components in current plane
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vint4 epd = endpnt1[pa_idx] - endpnt0[pa_idx];
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epd = select(epd, vint4::zero(), plane_mask);
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endpnt0f[pa_idx] = int_to_float(endpnt0[pa_idx]);
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offset[pa_idx] = int_to_float(epd) * (1.0f / 64.0f);
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}
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// Create an unquantized weight grid for this decimation level
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ASTCENC_ALIGNAS float uq_weightsf[BLOCK_MAX_WEIGHTS];
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for (unsigned int we_idx = 0; we_idx < weight_count; we_idx += ASTCENC_SIMD_WIDTH)
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{
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vint unquant_value(dec_weights_uquant + we_idx);
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vfloat unquant_valuef = int_to_float(unquant_value);
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storea(unquant_valuef, uq_weightsf + we_idx);
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}
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// For each weight compute previous, current, and next errors
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for (unsigned int we_idx = 0; we_idx < weight_count; we_idx++)
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{
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int uqw = dec_weights_uquant[we_idx];
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uint32_t prev_and_next = qat.prev_next_values[uqw];
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float uqw_base = uq_weightsf[we_idx];
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float uqw_down = static_cast<float>(prev_and_next & 0xFF);
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float uqw_up = static_cast<float>((prev_and_next >> 8) & 0xFF);
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float uqw_diff_down = uqw_down - uqw_base;
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float uqw_diff_up = uqw_up - uqw_base;
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vfloat4 error_basev = vfloat4::zero();
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vfloat4 error_downv = vfloat4::zero();
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vfloat4 error_upv = vfloat4::zero();
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// Interpolate the colors to create the diffs
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unsigned int texels_to_evaluate = di.weight_texel_count[we_idx];
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promise(texels_to_evaluate > 0);
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for (unsigned int te_idx = 0; te_idx < texels_to_evaluate; te_idx++)
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{
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unsigned int texel = di.weight_texels_tr[te_idx][we_idx];
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float tw_base = di.texel_contrib_for_weight[te_idx][we_idx];
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float weight_base = (uq_weightsf[di.texel_weights_tr[0][texel]] * di.texel_weight_contribs_float_tr[0][texel]
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+ uq_weightsf[di.texel_weights_tr[1][texel]] * di.texel_weight_contribs_float_tr[1][texel])
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+ (uq_weightsf[di.texel_weights_tr[2][texel]] * di.texel_weight_contribs_float_tr[2][texel]
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+ uq_weightsf[di.texel_weights_tr[3][texel]] * di.texel_weight_contribs_float_tr[3][texel]);
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// Ideally this is integer rounded, but IQ gain it isn't worth the overhead
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// float weight = astc::flt_rd(weight_base + 0.5f);
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// float weight_down = astc::flt_rd(weight_base + 0.5f + uqw_diff_down * tw_base) - weight;
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// float weight_up = astc::flt_rd(weight_base + 0.5f + uqw_diff_up * tw_base) - weight;
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float weight_down = weight_base + uqw_diff_down * tw_base - weight_base;
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float weight_up = weight_base + uqw_diff_up * tw_base - weight_base;
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unsigned int partition = pi.partition_of_texel[texel];
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vfloat4 color_offset = offset[partition];
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vfloat4 color_base = endpnt0f[partition];
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vfloat4 color = color_base + color_offset * weight_base;
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vfloat4 orig_color = blk.texel(texel);
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vfloat4 color_diff = color - orig_color;
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vfloat4 color_down_diff = color_diff + color_offset * weight_down;
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vfloat4 color_up_diff = color_diff + color_offset * weight_up;
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error_basev += color_diff * color_diff;
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error_downv += color_down_diff * color_down_diff;
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error_upv += color_up_diff * color_up_diff;
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}
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vfloat4 error_weight = blk.channel_weight;
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float error_base = hadd_s(error_basev * error_weight);
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float error_down = hadd_s(error_downv * error_weight);
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float error_up = hadd_s(error_upv * error_weight);
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// Check if the prev or next error is better, and if so use it
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if ((error_up < error_base) && (error_up < error_down) && (uqw < 64))
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{
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uq_weightsf[we_idx] = uqw_up;
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dec_weights_uquant[we_idx] = static_cast<uint8_t>(uqw_up);
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adjustments = true;
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}
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else if ((error_down < error_base) && (uqw > 0))
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{
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uq_weightsf[we_idx] = uqw_down;
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dec_weights_uquant[we_idx] = static_cast<uint8_t>(uqw_down);
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adjustments = true;
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}
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}
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// Prepare iteration for plane 2
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dec_weights_uquant += WEIGHTS_PLANE2_OFFSET;
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plane_mask = ~plane_mask;
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}
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return adjustments;
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}
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/**
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* @brief Compress a block using a chosen partitioning and 1 plane of weights.
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*
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* @param config The compressor configuration.
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* @param bsd The block size information.
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* @param blk The image block color data to compress.
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* @param only_always True if we only use "always" percentile block modes.
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* @param tune_errorval_threshold The error value threshold.
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* @param partition_count The partition count.
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* @param partition_index The partition index if @c partition_count is 2-4.
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* @param[out] scb The symbolic compressed block output.
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* @param[out] tmpbuf The quantized weights for plane 1.
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*/
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static float compress_symbolic_block_for_partition_1plane(
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const astcenc_config& config,
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const block_size_descriptor& bsd,
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const image_block& blk,
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bool only_always,
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float tune_errorval_threshold,
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unsigned int partition_count,
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unsigned int partition_index,
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symbolic_compressed_block& scb,
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compression_working_buffers& tmpbuf,
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int quant_limit
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) {
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promise(partition_count > 0);
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promise(config.tune_candidate_limit > 0);
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promise(config.tune_refinement_limit > 0);
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int max_weight_quant = astc::min(static_cast<int>(QUANT_32), quant_limit);
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auto compute_difference = &compute_symbolic_block_difference_1plane;
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if ((partition_count == 1) && !(config.flags & ASTCENC_FLG_MAP_RGBM))
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{
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compute_difference = &compute_symbolic_block_difference_1plane_1partition;
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}
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const auto& pi = bsd.get_partition_info(partition_count, partition_index);
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// Compute ideal weights and endpoint colors, with no quantization or decimation
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endpoints_and_weights& ei = tmpbuf.ei1;
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compute_ideal_colors_and_weights_1plane(blk, pi, ei);
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// Compute ideal weights and endpoint colors for every decimation
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float* dec_weights_ideal = tmpbuf.dec_weights_ideal;
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uint8_t* dec_weights_uquant = tmpbuf.dec_weights_uquant;
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// For each decimation mode, compute an ideal set of weights with no quantization
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unsigned int max_decimation_modes = only_always ? bsd.decimation_mode_count_always
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: bsd.decimation_mode_count_selected;
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promise(max_decimation_modes > 0);
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for (unsigned int i = 0; i < max_decimation_modes; i++)
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{
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const auto& dm = bsd.get_decimation_mode(i);
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if (!dm.is_ref_1plane(static_cast<quant_method>(max_weight_quant)))
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{
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continue;
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}
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const auto& di = bsd.get_decimation_info(i);
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compute_ideal_weights_for_decimation(
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ei,
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di,
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dec_weights_ideal + i * BLOCK_MAX_WEIGHTS);
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}
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// Compute maximum colors for the endpoints and ideal weights, then for each endpoint and ideal
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// weight pair, compute the smallest weight that will result in a color value greater than 1
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vfloat4 min_ep(10.0f);
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for (unsigned int i = 0; i < partition_count; i++)
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{
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vfloat4 ep = (vfloat4(1.0f) - ei.ep.endpt0[i]) / (ei.ep.endpt1[i] - ei.ep.endpt0[i]);
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vmask4 use_ep = (ep > vfloat4(0.5f)) & (ep < min_ep);
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min_ep = select(min_ep, ep, use_ep);
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}
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float min_wt_cutoff = hmin_s(min_ep);
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// For each mode, use the angular method to compute a shift
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compute_angular_endpoints_1plane(
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only_always, bsd, dec_weights_ideal, max_weight_quant, tmpbuf);
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float* weight_low_value = tmpbuf.weight_low_value1;
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float* weight_high_value = tmpbuf.weight_high_value1;
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int8_t* qwt_bitcounts = tmpbuf.qwt_bitcounts;
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float* qwt_errors = tmpbuf.qwt_errors;
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// For each mode (which specifies a decimation and a quantization):
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// * Compute number of bits needed for the quantized weights
|
|
// * Generate an optimized set of quantized weights
|
|
// * Compute quantization errors for the mode
|
|
|
|
|
|
static const int8_t free_bits_for_partition_count[4] {
|
|
115 - 4, 111 - 4 - PARTITION_INDEX_BITS, 108 - 4 - PARTITION_INDEX_BITS, 105 - 4 - PARTITION_INDEX_BITS
|
|
};
|
|
|
|
unsigned int max_block_modes = only_always ? bsd.block_mode_count_1plane_always
|
|
: bsd.block_mode_count_1plane_selected;
|
|
promise(max_block_modes > 0);
|
|
for (unsigned int i = 0; i < max_block_modes; i++)
|
|
{
|
|
const block_mode& bm = bsd.block_modes[i];
|
|
|
|
if (bm.quant_mode > max_weight_quant)
|
|
{
|
|
qwt_errors[i] = 1e38f;
|
|
continue;
|
|
}
|
|
|
|
assert(!bm.is_dual_plane);
|
|
int bitcount = free_bits_for_partition_count[partition_count - 1] - bm.weight_bits;
|
|
if (bitcount <= 0)
|
|
{
|
|
qwt_errors[i] = 1e38f;
|
|
continue;
|
|
}
|
|
|
|
if (weight_high_value[i] > 1.02f * min_wt_cutoff)
|
|
{
|
|
weight_high_value[i] = 1.0f;
|
|
}
|
|
|
|
int decimation_mode = bm.decimation_mode;
|
|
const auto& di = bsd.get_decimation_info(decimation_mode);
|
|
|
|
qwt_bitcounts[i] = static_cast<int8_t>(bitcount);
|
|
|
|
ASTCENC_ALIGNAS float dec_weights_uquantf[BLOCK_MAX_WEIGHTS];
|
|
|
|
// Generate the optimized set of weights for the weight mode
|
|
compute_quantized_weights_for_decimation(
|
|
di,
|
|
weight_low_value[i], weight_high_value[i],
|
|
dec_weights_ideal + BLOCK_MAX_WEIGHTS * decimation_mode,
|
|
dec_weights_uquantf,
|
|
dec_weights_uquant + BLOCK_MAX_WEIGHTS * i,
|
|
bm.get_weight_quant_mode());
|
|
|
|
// Compute weight quantization errors for the block mode
|
|
qwt_errors[i] = compute_error_of_weight_set_1plane(
|
|
ei,
|
|
di,
|
|
dec_weights_uquantf);
|
|
}
|
|
|
|
// Decide the optimal combination of color endpoint encodings and weight encodings
|
|
uint8_t partition_format_specifiers[TUNE_MAX_TRIAL_CANDIDATES][BLOCK_MAX_PARTITIONS];
|
|
int block_mode_index[TUNE_MAX_TRIAL_CANDIDATES];
|
|
|
|
quant_method color_quant_level[TUNE_MAX_TRIAL_CANDIDATES];
|
|
quant_method color_quant_level_mod[TUNE_MAX_TRIAL_CANDIDATES];
|
|
|
|
unsigned int candidate_count = compute_ideal_endpoint_formats(
|
|
pi, blk, ei.ep, qwt_bitcounts, qwt_errors,
|
|
config.tune_candidate_limit, 0, max_block_modes,
|
|
partition_format_specifiers, block_mode_index,
|
|
color_quant_level, color_quant_level_mod, tmpbuf);
|
|
|
|
// Iterate over the N believed-to-be-best modes to find out which one is actually best
|
|
float best_errorval_in_mode = ERROR_CALC_DEFAULT;
|
|
float best_errorval_in_scb = scb.errorval;
|
|
|
|
for (unsigned int i = 0; i < candidate_count; i++)
|
|
{
|
|
TRACE_NODE(node0, "candidate");
|
|
|
|
const int bm_packed_index = block_mode_index[i];
|
|
assert(bm_packed_index >= 0 && bm_packed_index < static_cast<int>(bsd.block_mode_count_1plane_selected));
|
|
const block_mode& qw_bm = bsd.block_modes[bm_packed_index];
|
|
|
|
int decimation_mode = qw_bm.decimation_mode;
|
|
const auto& di = bsd.get_decimation_info(decimation_mode);
|
|
promise(di.weight_count > 0);
|
|
|
|
trace_add_data("weight_x", di.weight_x);
|
|
trace_add_data("weight_y", di.weight_y);
|
|
trace_add_data("weight_z", di.weight_z);
|
|
trace_add_data("weight_quant", qw_bm.quant_mode);
|
|
|
|
// Recompute the ideal color endpoints before storing them
|
|
vfloat4 rgbs_colors[BLOCK_MAX_PARTITIONS];
|
|
vfloat4 rgbo_colors[BLOCK_MAX_PARTITIONS];
|
|
|
|
symbolic_compressed_block workscb;
|
|
endpoints workep = ei.ep;
|
|
|
|
uint8_t* u8_weight_src = dec_weights_uquant + BLOCK_MAX_WEIGHTS * bm_packed_index;
|
|
|
|
for (unsigned int j = 0; j < di.weight_count; j++)
|
|
{
|
|
workscb.weights[j] = u8_weight_src[j];
|
|
}
|
|
|
|
for (unsigned int l = 0; l < config.tune_refinement_limit; l++)
|
|
{
|
|
recompute_ideal_colors_1plane(
|
|
blk, pi, di, workscb.weights,
|
|
workep, rgbs_colors, rgbo_colors);
|
|
|
|
// Quantize the chosen color, tracking if worth trying the mod value
|
|
bool all_same = color_quant_level[i] != color_quant_level_mod[i];
|
|
for (unsigned int j = 0; j < partition_count; j++)
|
|
{
|
|
workscb.color_formats[j] = pack_color_endpoints(
|
|
workep.endpt0[j],
|
|
workep.endpt1[j],
|
|
rgbs_colors[j],
|
|
rgbo_colors[j],
|
|
partition_format_specifiers[i][j],
|
|
workscb.color_values[j],
|
|
color_quant_level[i]);
|
|
|
|
all_same = all_same && workscb.color_formats[j] == workscb.color_formats[0];
|
|
}
|
|
|
|
// If all the color endpoint modes are the same, we get a few more bits to store colors;
|
|
// let's see if we can take advantage of this: requantize all the colors and see if the
|
|
// endpoint modes remain the same.
|
|
workscb.color_formats_matched = 0;
|
|
if (partition_count >= 2 && all_same)
|
|
{
|
|
uint8_t colorvals[BLOCK_MAX_PARTITIONS][8];
|
|
uint8_t color_formats_mod[BLOCK_MAX_PARTITIONS] { 0 };
|
|
bool all_same_mod = true;
|
|
for (unsigned int j = 0; j < partition_count; j++)
|
|
{
|
|
color_formats_mod[j] = pack_color_endpoints(
|
|
workep.endpt0[j],
|
|
workep.endpt1[j],
|
|
rgbs_colors[j],
|
|
rgbo_colors[j],
|
|
partition_format_specifiers[i][j],
|
|
colorvals[j],
|
|
color_quant_level_mod[i]);
|
|
|
|
// Early out as soon as it's no longer possible to use mod
|
|
if (color_formats_mod[j] != color_formats_mod[0])
|
|
{
|
|
all_same_mod = false;
|
|
break;
|
|
}
|
|
}
|
|
|
|
if (all_same_mod)
|
|
{
|
|
workscb.color_formats_matched = 1;
|
|
for (unsigned int j = 0; j < BLOCK_MAX_PARTITIONS; j++)
|
|
{
|
|
for (unsigned int k = 0; k < 8; k++)
|
|
{
|
|
workscb.color_values[j][k] = colorvals[j][k];
|
|
}
|
|
|
|
workscb.color_formats[j] = color_formats_mod[j];
|
|
}
|
|
}
|
|
}
|
|
|
|
// Store header fields
|
|
workscb.partition_count = static_cast<uint8_t>(partition_count);
|
|
workscb.partition_index = static_cast<uint16_t>(partition_index);
|
|
workscb.plane2_component = -1;
|
|
workscb.quant_mode = workscb.color_formats_matched ? color_quant_level_mod[i] : color_quant_level[i];
|
|
workscb.block_mode = qw_bm.mode_index;
|
|
workscb.block_type = SYM_BTYPE_NONCONST;
|
|
|
|
// Pre-realign test
|
|
if (l == 0)
|
|
{
|
|
float errorval = compute_difference(config, bsd, workscb, blk);
|
|
if (errorval == -ERROR_CALC_DEFAULT)
|
|
{
|
|
errorval = -errorval;
|
|
workscb.block_type = SYM_BTYPE_ERROR;
|
|
}
|
|
|
|
trace_add_data("error_prerealign", errorval);
|
|
best_errorval_in_mode = astc::min(errorval, best_errorval_in_mode);
|
|
|
|
// Average refinement improvement is 3.5% per iteration (allow 4.5%), but the first
|
|
// iteration can help more so we give it a extra 8% leeway. Use this knowledge to
|
|
// drive a heuristic to skip blocks that are unlikely to catch up with the best
|
|
// block we have already.
|
|
unsigned int iters_remaining = config.tune_refinement_limit - l;
|
|
float threshold = (0.045f * static_cast<float>(iters_remaining)) + 1.08f;
|
|
if (errorval > (threshold * best_errorval_in_scb))
|
|
{
|
|
break;
|
|
}
|
|
|
|
if (errorval < best_errorval_in_scb)
|
|
{
|
|
best_errorval_in_scb = errorval;
|
|
workscb.errorval = errorval;
|
|
scb = workscb;
|
|
|
|
if (errorval < tune_errorval_threshold)
|
|
{
|
|
// Skip remaining candidates - this is "good enough"
|
|
i = candidate_count;
|
|
break;
|
|
}
|
|
}
|
|
}
|
|
|
|
bool adjustments;
|
|
if (di.weight_count != bsd.texel_count)
|
|
{
|
|
adjustments = realign_weights_decimated(
|
|
config.profile, bsd, blk, workscb);
|
|
}
|
|
else
|
|
{
|
|
adjustments = realign_weights_undecimated(
|
|
config.profile, bsd, blk, workscb);
|
|
}
|
|
|
|
// Post-realign test
|
|
float errorval = compute_difference(config, bsd, workscb, blk);
|
|
if (errorval == -ERROR_CALC_DEFAULT)
|
|
{
|
|
errorval = -errorval;
|
|
workscb.block_type = SYM_BTYPE_ERROR;
|
|
}
|
|
|
|
trace_add_data("error_postrealign", errorval);
|
|
best_errorval_in_mode = astc::min(errorval, best_errorval_in_mode);
|
|
|
|
// Average refinement improvement is 3.5% per iteration, so skip blocks that are
|
|
// unlikely to catch up with the best block we have already. Assume a 4.5% per step to
|
|
// give benefit of the doubt ...
|
|
unsigned int iters_remaining = config.tune_refinement_limit - 1 - l;
|
|
float threshold = (0.045f * static_cast<float>(iters_remaining)) + 1.0f;
|
|
if (errorval > (threshold * best_errorval_in_scb))
|
|
{
|
|
break;
|
|
}
|
|
|
|
if (errorval < best_errorval_in_scb)
|
|
{
|
|
best_errorval_in_scb = errorval;
|
|
workscb.errorval = errorval;
|
|
scb = workscb;
|
|
|
|
if (errorval < tune_errorval_threshold)
|
|
{
|
|
// Skip remaining candidates - this is "good enough"
|
|
i = candidate_count;
|
|
break;
|
|
}
|
|
}
|
|
|
|
if (!adjustments)
|
|
{
|
|
break;
|
|
}
|
|
}
|
|
}
|
|
|
|
return best_errorval_in_mode;
|
|
}
|
|
|
|
/**
|
|
* @brief Compress a block using a chosen partitioning and 2 planes of weights.
|
|
*
|
|
* @param config The compressor configuration.
|
|
* @param bsd The block size information.
|
|
* @param blk The image block color data to compress.
|
|
* @param tune_errorval_threshold The error value threshold.
|
|
* @param plane2_component The component index for the second plane of weights.
|
|
* @param[out] scb The symbolic compressed block output.
|
|
* @param[out] tmpbuf The quantized weights for plane 1.
|
|
*/
|
|
static float compress_symbolic_block_for_partition_2planes(
|
|
const astcenc_config& config,
|
|
const block_size_descriptor& bsd,
|
|
const image_block& blk,
|
|
float tune_errorval_threshold,
|
|
unsigned int plane2_component,
|
|
symbolic_compressed_block& scb,
|
|
compression_working_buffers& tmpbuf,
|
|
int quant_limit
|
|
) {
|
|
promise(config.tune_candidate_limit > 0);
|
|
promise(config.tune_refinement_limit > 0);
|
|
promise(bsd.decimation_mode_count_selected > 0);
|
|
|
|
int max_weight_quant = astc::min(static_cast<int>(QUANT_32), quant_limit);
|
|
|
|
// Compute ideal weights and endpoint colors, with no quantization or decimation
|
|
endpoints_and_weights& ei1 = tmpbuf.ei1;
|
|
endpoints_and_weights& ei2 = tmpbuf.ei2;
|
|
|
|
compute_ideal_colors_and_weights_2planes(bsd, blk, plane2_component, ei1, ei2);
|
|
|
|
// Compute ideal weights and endpoint colors for every decimation
|
|
float* dec_weights_ideal = tmpbuf.dec_weights_ideal;
|
|
uint8_t* dec_weights_uquant = tmpbuf.dec_weights_uquant;
|
|
|
|
// For each decimation mode, compute an ideal set of weights with no quantization
|
|
for (unsigned int i = 0; i < bsd.decimation_mode_count_selected; i++)
|
|
{
|
|
const auto& dm = bsd.get_decimation_mode(i);
|
|
if (!dm.is_ref_2plane(static_cast<quant_method>(max_weight_quant)))
|
|
{
|
|
continue;
|
|
}
|
|
|
|
const auto& di = bsd.get_decimation_info(i);
|
|
|
|
compute_ideal_weights_for_decimation(
|
|
ei1,
|
|
di,
|
|
dec_weights_ideal + i * BLOCK_MAX_WEIGHTS);
|
|
|
|
compute_ideal_weights_for_decimation(
|
|
ei2,
|
|
di,
|
|
dec_weights_ideal + i * BLOCK_MAX_WEIGHTS + WEIGHTS_PLANE2_OFFSET);
|
|
}
|
|
|
|
// Compute maximum colors for the endpoints and ideal weights, then for each endpoint and ideal
|
|
// weight pair, compute the smallest weight that will result in a color value greater than 1
|
|
vfloat4 min_ep1(10.0f);
|
|
vfloat4 min_ep2(10.0f);
|
|
|
|
vfloat4 ep1 = (vfloat4(1.0f) - ei1.ep.endpt0[0]) / (ei1.ep.endpt1[0] - ei1.ep.endpt0[0]);
|
|
vmask4 use_ep1 = (ep1 > vfloat4(0.5f)) & (ep1 < min_ep1);
|
|
min_ep1 = select(min_ep1, ep1, use_ep1);
|
|
|
|
vfloat4 ep2 = (vfloat4(1.0f) - ei2.ep.endpt0[0]) / (ei2.ep.endpt1[0] - ei2.ep.endpt0[0]);
|
|
vmask4 use_ep2 = (ep2 > vfloat4(0.5f)) & (ep2 < min_ep2);
|
|
min_ep2 = select(min_ep2, ep2, use_ep2);
|
|
|
|
vfloat4 err_max(ERROR_CALC_DEFAULT);
|
|
vmask4 err_mask = vint4::lane_id() == vint4(plane2_component);
|
|
|
|
// Set the plane2 component to max error in ep1
|
|
min_ep1 = select(min_ep1, err_max, err_mask);
|
|
|
|
float min_wt_cutoff1 = hmin_s(min_ep1);
|
|
|
|
// Set the minwt2 to the plane2 component min in ep2
|
|
float min_wt_cutoff2 = hmin_s(select(err_max, min_ep2, err_mask));
|
|
|
|
compute_angular_endpoints_2planes(
|
|
bsd, dec_weights_ideal, max_weight_quant, tmpbuf);
|
|
|
|
// For each mode (which specifies a decimation and a quantization):
|
|
// * Compute number of bits needed for the quantized weights
|
|
// * Generate an optimized set of quantized weights
|
|
// * Compute quantization errors for the mode
|
|
|
|
float* weight_low_value1 = tmpbuf.weight_low_value1;
|
|
float* weight_high_value1 = tmpbuf.weight_high_value1;
|
|
float* weight_low_value2 = tmpbuf.weight_low_value2;
|
|
float* weight_high_value2 = tmpbuf.weight_high_value2;
|
|
|
|
int8_t* qwt_bitcounts = tmpbuf.qwt_bitcounts;
|
|
float* qwt_errors = tmpbuf.qwt_errors;
|
|
|
|
unsigned int start_2plane = bsd.block_mode_count_1plane_selected;
|
|
unsigned int end_2plane = bsd.block_mode_count_1plane_2plane_selected;
|
|
|
|
for (unsigned int i = start_2plane; i < end_2plane; i++)
|
|
{
|
|
const block_mode& bm = bsd.block_modes[i];
|
|
assert(bm.is_dual_plane);
|
|
|
|
if (bm.quant_mode > max_weight_quant)
|
|
{
|
|
qwt_errors[i] = 1e38f;
|
|
continue;
|
|
}
|
|
|
|
qwt_bitcounts[i] = static_cast<int8_t>(109 - bm.weight_bits);
|
|
|
|
if (weight_high_value1[i] > 1.02f * min_wt_cutoff1)
|
|
{
|
|
weight_high_value1[i] = 1.0f;
|
|
}
|
|
|
|
if (weight_high_value2[i] > 1.02f * min_wt_cutoff2)
|
|
{
|
|
weight_high_value2[i] = 1.0f;
|
|
}
|
|
|
|
unsigned int decimation_mode = bm.decimation_mode;
|
|
const auto& di = bsd.get_decimation_info(decimation_mode);
|
|
|
|
ASTCENC_ALIGNAS float dec_weights_uquantf[BLOCK_MAX_WEIGHTS];
|
|
|
|
// Generate the optimized set of weights for the mode
|
|
compute_quantized_weights_for_decimation(
|
|
di,
|
|
weight_low_value1[i],
|
|
weight_high_value1[i],
|
|
dec_weights_ideal + BLOCK_MAX_WEIGHTS * decimation_mode,
|
|
dec_weights_uquantf,
|
|
dec_weights_uquant + BLOCK_MAX_WEIGHTS * i,
|
|
bm.get_weight_quant_mode());
|
|
|
|
compute_quantized_weights_for_decimation(
|
|
di,
|
|
weight_low_value2[i],
|
|
weight_high_value2[i],
|
|
dec_weights_ideal + BLOCK_MAX_WEIGHTS * decimation_mode + WEIGHTS_PLANE2_OFFSET,
|
|
dec_weights_uquantf + WEIGHTS_PLANE2_OFFSET,
|
|
dec_weights_uquant + BLOCK_MAX_WEIGHTS * i + WEIGHTS_PLANE2_OFFSET,
|
|
bm.get_weight_quant_mode());
|
|
|
|
// Compute weight quantization errors for the block mode
|
|
qwt_errors[i] = compute_error_of_weight_set_2planes(
|
|
ei1,
|
|
ei2,
|
|
di,
|
|
dec_weights_uquantf,
|
|
dec_weights_uquantf + WEIGHTS_PLANE2_OFFSET);
|
|
}
|
|
|
|
// Decide the optimal combination of color endpoint encodings and weight encodings
|
|
uint8_t partition_format_specifiers[TUNE_MAX_TRIAL_CANDIDATES][BLOCK_MAX_PARTITIONS];
|
|
int block_mode_index[TUNE_MAX_TRIAL_CANDIDATES];
|
|
|
|
quant_method color_quant_level[TUNE_MAX_TRIAL_CANDIDATES];
|
|
quant_method color_quant_level_mod[TUNE_MAX_TRIAL_CANDIDATES];
|
|
|
|
endpoints epm;
|
|
merge_endpoints(ei1.ep, ei2.ep, plane2_component, epm);
|
|
|
|
const auto& pi = bsd.get_partition_info(1, 0);
|
|
unsigned int candidate_count = compute_ideal_endpoint_formats(
|
|
pi, blk, epm, qwt_bitcounts, qwt_errors,
|
|
config.tune_candidate_limit,
|
|
bsd.block_mode_count_1plane_selected, bsd.block_mode_count_1plane_2plane_selected,
|
|
partition_format_specifiers, block_mode_index,
|
|
color_quant_level, color_quant_level_mod, tmpbuf);
|
|
|
|
// Iterate over the N believed-to-be-best modes to find out which one is actually best
|
|
float best_errorval_in_mode = ERROR_CALC_DEFAULT;
|
|
float best_errorval_in_scb = scb.errorval;
|
|
|
|
for (unsigned int i = 0; i < candidate_count; i++)
|
|
{
|
|
TRACE_NODE(node0, "candidate");
|
|
|
|
const int bm_packed_index = block_mode_index[i];
|
|
assert(bm_packed_index >= static_cast<int>(bsd.block_mode_count_1plane_selected) &&
|
|
bm_packed_index < static_cast<int>(bsd.block_mode_count_1plane_2plane_selected));
|
|
const block_mode& qw_bm = bsd.block_modes[bm_packed_index];
|
|
|
|
int decimation_mode = qw_bm.decimation_mode;
|
|
const auto& di = bsd.get_decimation_info(decimation_mode);
|
|
promise(di.weight_count > 0);
|
|
|
|
trace_add_data("weight_x", di.weight_x);
|
|
trace_add_data("weight_y", di.weight_y);
|
|
trace_add_data("weight_z", di.weight_z);
|
|
trace_add_data("weight_quant", qw_bm.quant_mode);
|
|
|
|
vfloat4 rgbs_color;
|
|
vfloat4 rgbo_color;
|
|
|
|
symbolic_compressed_block workscb;
|
|
endpoints workep = epm;
|
|
|
|
uint8_t* u8_weight1_src = dec_weights_uquant + BLOCK_MAX_WEIGHTS * bm_packed_index;
|
|
uint8_t* u8_weight2_src = dec_weights_uquant + BLOCK_MAX_WEIGHTS * bm_packed_index + WEIGHTS_PLANE2_OFFSET;
|
|
|
|
for (int j = 0; j < di.weight_count; j++)
|
|
{
|
|
workscb.weights[j] = u8_weight1_src[j];
|
|
workscb.weights[j + WEIGHTS_PLANE2_OFFSET] = u8_weight2_src[j];
|
|
}
|
|
|
|
for (unsigned int l = 0; l < config.tune_refinement_limit; l++)
|
|
{
|
|
recompute_ideal_colors_2planes(
|
|
blk, bsd, di,
|
|
workscb.weights, workscb.weights + WEIGHTS_PLANE2_OFFSET,
|
|
workep, rgbs_color, rgbo_color, plane2_component);
|
|
|
|
// Quantize the chosen color
|
|
workscb.color_formats[0] = pack_color_endpoints(
|
|
workep.endpt0[0],
|
|
workep.endpt1[0],
|
|
rgbs_color, rgbo_color,
|
|
partition_format_specifiers[i][0],
|
|
workscb.color_values[0],
|
|
color_quant_level[i]);
|
|
|
|
// Store header fields
|
|
workscb.partition_count = 1;
|
|
workscb.partition_index = 0;
|
|
workscb.quant_mode = color_quant_level[i];
|
|
workscb.color_formats_matched = 0;
|
|
workscb.block_mode = qw_bm.mode_index;
|
|
workscb.plane2_component = static_cast<int8_t>(plane2_component);
|
|
workscb.block_type = SYM_BTYPE_NONCONST;
|
|
|
|
// Pre-realign test
|
|
if (l == 0)
|
|
{
|
|
float errorval = compute_symbolic_block_difference_2plane(config, bsd, workscb, blk);
|
|
if (errorval == -ERROR_CALC_DEFAULT)
|
|
{
|
|
errorval = -errorval;
|
|
workscb.block_type = SYM_BTYPE_ERROR;
|
|
}
|
|
|
|
trace_add_data("error_prerealign", errorval);
|
|
best_errorval_in_mode = astc::min(errorval, best_errorval_in_mode);
|
|
|
|
// Average refinement improvement is 3.5% per iteration (allow 4.5%), but the first
|
|
// iteration can help more so we give it a extra 8% leeway. Use this knowledge to
|
|
// drive a heuristic to skip blocks that are unlikely to catch up with the best
|
|
// block we have already.
|
|
unsigned int iters_remaining = config.tune_refinement_limit - l;
|
|
float threshold = (0.045f * static_cast<float>(iters_remaining)) + 1.08f;
|
|
if (errorval > (threshold * best_errorval_in_scb))
|
|
{
|
|
break;
|
|
}
|
|
|
|
if (errorval < best_errorval_in_scb)
|
|
{
|
|
best_errorval_in_scb = errorval;
|
|
workscb.errorval = errorval;
|
|
scb = workscb;
|
|
|
|
if (errorval < tune_errorval_threshold)
|
|
{
|
|
// Skip remaining candidates - this is "good enough"
|
|
i = candidate_count;
|
|
break;
|
|
}
|
|
}
|
|
}
|
|
|
|
// Perform a final pass over the weights to try to improve them.
|
|
bool adjustments;
|
|
if (di.weight_count != bsd.texel_count)
|
|
{
|
|
adjustments = realign_weights_decimated(
|
|
config.profile, bsd, blk, workscb);
|
|
}
|
|
else
|
|
{
|
|
adjustments = realign_weights_undecimated(
|
|
config.profile, bsd, blk, workscb);
|
|
}
|
|
|
|
// Post-realign test
|
|
float errorval = compute_symbolic_block_difference_2plane(config, bsd, workscb, blk);
|
|
if (errorval == -ERROR_CALC_DEFAULT)
|
|
{
|
|
errorval = -errorval;
|
|
workscb.block_type = SYM_BTYPE_ERROR;
|
|
}
|
|
|
|
trace_add_data("error_postrealign", errorval);
|
|
best_errorval_in_mode = astc::min(errorval, best_errorval_in_mode);
|
|
|
|
// Average refinement improvement is 3.5% per iteration, so skip blocks that are
|
|
// unlikely to catch up with the best block we have already. Assume a 4.5% per step to
|
|
// give benefit of the doubt ...
|
|
unsigned int iters_remaining = config.tune_refinement_limit - 1 - l;
|
|
float threshold = (0.045f * static_cast<float>(iters_remaining)) + 1.0f;
|
|
if (errorval > (threshold * best_errorval_in_scb))
|
|
{
|
|
break;
|
|
}
|
|
|
|
if (errorval < best_errorval_in_scb)
|
|
{
|
|
best_errorval_in_scb = errorval;
|
|
workscb.errorval = errorval;
|
|
scb = workscb;
|
|
|
|
if (errorval < tune_errorval_threshold)
|
|
{
|
|
// Skip remaining candidates - this is "good enough"
|
|
i = candidate_count;
|
|
break;
|
|
}
|
|
}
|
|
|
|
if (!adjustments)
|
|
{
|
|
break;
|
|
}
|
|
}
|
|
}
|
|
|
|
return best_errorval_in_mode;
|
|
}
|
|
|
|
/**
|
|
* @brief Determine the lowest cross-channel correlation factor.
|
|
*
|
|
* @param texels_per_block The number of texels in a block.
|
|
* @param blk The image block color data to compress.
|
|
*
|
|
* @return Return the lowest correlation factor.
|
|
*/
|
|
static float prepare_block_statistics(
|
|
int texels_per_block,
|
|
const image_block& blk
|
|
) {
|
|
// Compute covariance matrix, as a collection of 10 scalars that form the upper-triangular row
|
|
// of the matrix. The matrix is symmetric, so this is all we need for this use case.
|
|
float rs = 0.0f;
|
|
float gs = 0.0f;
|
|
float bs = 0.0f;
|
|
float as = 0.0f;
|
|
float rr_var = 0.0f;
|
|
float gg_var = 0.0f;
|
|
float bb_var = 0.0f;
|
|
float aa_var = 0.0f;
|
|
float rg_cov = 0.0f;
|
|
float rb_cov = 0.0f;
|
|
float ra_cov = 0.0f;
|
|
float gb_cov = 0.0f;
|
|
float ga_cov = 0.0f;
|
|
float ba_cov = 0.0f;
|
|
|
|
float weight_sum = 0.0f;
|
|
|
|
promise(texels_per_block > 0);
|
|
for (int i = 0; i < texels_per_block; i++)
|
|
{
|
|
float weight = hadd_s(blk.channel_weight) / 4.0f;
|
|
assert(weight >= 0.0f);
|
|
weight_sum += weight;
|
|
|
|
float r = blk.data_r[i];
|
|
float g = blk.data_g[i];
|
|
float b = blk.data_b[i];
|
|
float a = blk.data_a[i];
|
|
|
|
float rw = r * weight;
|
|
rs += rw;
|
|
rr_var += r * rw;
|
|
rg_cov += g * rw;
|
|
rb_cov += b * rw;
|
|
ra_cov += a * rw;
|
|
|
|
float gw = g * weight;
|
|
gs += gw;
|
|
gg_var += g * gw;
|
|
gb_cov += b * gw;
|
|
ga_cov += a * gw;
|
|
|
|
float bw = b * weight;
|
|
bs += bw;
|
|
bb_var += b * bw;
|
|
ba_cov += a * bw;
|
|
|
|
float aw = a * weight;
|
|
as += aw;
|
|
aa_var += a * aw;
|
|
}
|
|
|
|
float rpt = 1.0f / astc::max(weight_sum, 1e-7f);
|
|
|
|
rr_var -= rs * (rs * rpt);
|
|
rg_cov -= gs * (rs * rpt);
|
|
rb_cov -= bs * (rs * rpt);
|
|
ra_cov -= as * (rs * rpt);
|
|
|
|
gg_var -= gs * (gs * rpt);
|
|
gb_cov -= bs * (gs * rpt);
|
|
ga_cov -= as * (gs * rpt);
|
|
|
|
bb_var -= bs * (bs * rpt);
|
|
ba_cov -= as * (bs * rpt);
|
|
|
|
aa_var -= as * (as * rpt);
|
|
|
|
// These will give a NaN if a channel is constant - these are fixed up in the next step
|
|
rg_cov *= astc::rsqrt(rr_var * gg_var);
|
|
rb_cov *= astc::rsqrt(rr_var * bb_var);
|
|
ra_cov *= astc::rsqrt(rr_var * aa_var);
|
|
gb_cov *= astc::rsqrt(gg_var * bb_var);
|
|
ga_cov *= astc::rsqrt(gg_var * aa_var);
|
|
ba_cov *= astc::rsqrt(bb_var * aa_var);
|
|
|
|
if (astc::isnan(rg_cov)) rg_cov = 1.0f;
|
|
if (astc::isnan(rb_cov)) rb_cov = 1.0f;
|
|
if (astc::isnan(ra_cov)) ra_cov = 1.0f;
|
|
if (astc::isnan(gb_cov)) gb_cov = 1.0f;
|
|
if (astc::isnan(ga_cov)) ga_cov = 1.0f;
|
|
if (astc::isnan(ba_cov)) ba_cov = 1.0f;
|
|
|
|
float lowest_correlation = astc::min(fabsf(rg_cov), fabsf(rb_cov));
|
|
lowest_correlation = astc::min(lowest_correlation, fabsf(ra_cov));
|
|
lowest_correlation = astc::min(lowest_correlation, fabsf(gb_cov));
|
|
lowest_correlation = astc::min(lowest_correlation, fabsf(ga_cov));
|
|
lowest_correlation = astc::min(lowest_correlation, fabsf(ba_cov));
|
|
|
|
// Diagnostic trace points
|
|
trace_add_data("min_r", blk.data_min.lane<0>());
|
|
trace_add_data("max_r", blk.data_max.lane<0>());
|
|
trace_add_data("min_g", blk.data_min.lane<1>());
|
|
trace_add_data("max_g", blk.data_max.lane<1>());
|
|
trace_add_data("min_b", blk.data_min.lane<2>());
|
|
trace_add_data("max_b", blk.data_max.lane<2>());
|
|
trace_add_data("min_a", blk.data_min.lane<3>());
|
|
trace_add_data("max_a", blk.data_max.lane<3>());
|
|
trace_add_data("cov_rg", fabsf(rg_cov));
|
|
trace_add_data("cov_rb", fabsf(rb_cov));
|
|
trace_add_data("cov_ra", fabsf(ra_cov));
|
|
trace_add_data("cov_gb", fabsf(gb_cov));
|
|
trace_add_data("cov_ga", fabsf(ga_cov));
|
|
trace_add_data("cov_ba", fabsf(ba_cov));
|
|
|
|
return lowest_correlation;
|
|
}
|
|
|
|
/* See header for documentation. */
|
|
void compress_block(
|
|
const astcenc_contexti& ctx,
|
|
const image_block& blk,
|
|
uint8_t pcb[16],
|
|
compression_working_buffers& tmpbuf)
|
|
{
|
|
astcenc_profile decode_mode = ctx.config.profile;
|
|
symbolic_compressed_block scb;
|
|
const block_size_descriptor& bsd = *ctx.bsd;
|
|
float lowest_correl;
|
|
|
|
TRACE_NODE(node0, "block");
|
|
trace_add_data("pos_x", blk.xpos);
|
|
trace_add_data("pos_y", blk.ypos);
|
|
trace_add_data("pos_z", blk.zpos);
|
|
|
|
// Set stricter block targets for luminance data as we have more bits to play with
|
|
bool block_is_l = blk.is_luminance();
|
|
float block_is_l_scale = block_is_l ? 1.0f / 1.5f : 1.0f;
|
|
|
|
// Set slightly stricter block targets for lumalpha data as we have more bits to play with
|
|
bool block_is_la = blk.is_luminancealpha();
|
|
float block_is_la_scale = block_is_la ? 1.0f / 1.05f : 1.0f;
|
|
|
|
bool block_skip_two_plane = false;
|
|
int max_partitions = ctx.config.tune_partition_count_limit;
|
|
|
|
unsigned int requested_partition_indices[3] {
|
|
ctx.config.tune_2partition_index_limit,
|
|
ctx.config.tune_3partition_index_limit,
|
|
ctx.config.tune_4partition_index_limit
|
|
};
|
|
|
|
unsigned int requested_partition_trials[3] {
|
|
ctx.config.tune_2partitioning_candidate_limit,
|
|
ctx.config.tune_3partitioning_candidate_limit,
|
|
ctx.config.tune_4partitioning_candidate_limit
|
|
};
|
|
|
|
#if defined(ASTCENC_DIAGNOSTICS)
|
|
// Do this early in diagnostic builds so we can dump uniform metrics
|
|
// for every block. Do it later in release builds to avoid redundant work!
|
|
float error_weight_sum = hadd_s(blk.channel_weight) * bsd.texel_count;
|
|
float error_threshold = ctx.config.tune_db_limit
|
|
* error_weight_sum
|
|
* block_is_l_scale
|
|
* block_is_la_scale;
|
|
|
|
lowest_correl = prepare_block_statistics(bsd.texel_count, blk);
|
|
trace_add_data("lowest_correl", lowest_correl);
|
|
trace_add_data("tune_error_threshold", error_threshold);
|
|
#endif
|
|
|
|
// Detected a constant-color block
|
|
if (all(blk.data_min == blk.data_max))
|
|
{
|
|
TRACE_NODE(node1, "pass");
|
|
trace_add_data("partition_count", 0);
|
|
trace_add_data("plane_count", 1);
|
|
|
|
scb.partition_count = 0;
|
|
|
|
// Encode as FP16 if using HDR
|
|
if ((decode_mode == ASTCENC_PRF_HDR) ||
|
|
(decode_mode == ASTCENC_PRF_HDR_RGB_LDR_A))
|
|
{
|
|
scb.block_type = SYM_BTYPE_CONST_F16;
|
|
vint4 color_f16 = float_to_float16(blk.origin_texel);
|
|
store(color_f16, scb.constant_color);
|
|
}
|
|
// Encode as UNORM16 if NOT using HDR
|
|
else
|
|
{
|
|
scb.block_type = SYM_BTYPE_CONST_U16;
|
|
vfloat4 color_f32 = clamp(0.0f, 1.0f, blk.origin_texel) * 65535.0f;
|
|
vint4 color_u16 = float_to_int_rtn(color_f32);
|
|
store(color_u16, scb.constant_color);
|
|
}
|
|
|
|
trace_add_data("exit", "quality hit");
|
|
|
|
symbolic_to_physical(bsd, scb, pcb);
|
|
return;
|
|
}
|
|
|
|
#if !defined(ASTCENC_DIAGNOSTICS)
|
|
float error_weight_sum = hadd_s(blk.channel_weight) * bsd.texel_count;
|
|
float error_threshold = ctx.config.tune_db_limit
|
|
* error_weight_sum
|
|
* block_is_l_scale
|
|
* block_is_la_scale;
|
|
#endif
|
|
|
|
// Set SCB and mode errors to a very high error value
|
|
scb.errorval = ERROR_CALC_DEFAULT;
|
|
scb.block_type = SYM_BTYPE_ERROR;
|
|
|
|
float best_errorvals_for_pcount[BLOCK_MAX_PARTITIONS] {
|
|
ERROR_CALC_DEFAULT, ERROR_CALC_DEFAULT, ERROR_CALC_DEFAULT, ERROR_CALC_DEFAULT
|
|
};
|
|
|
|
float exit_thresholds_for_pcount[BLOCK_MAX_PARTITIONS] {
|
|
0.0f,
|
|
ctx.config.tune_2partition_early_out_limit_factor,
|
|
ctx.config.tune_3partition_early_out_limit_factor,
|
|
0.0f
|
|
};
|
|
|
|
// Trial using 1 plane of weights and 1 partition.
|
|
|
|
// Most of the time we test it twice, first with a mode cutoff of 0 and then with the specified
|
|
// mode cutoff. This causes an early-out that speeds up encoding of easy blocks. However, this
|
|
// optimization is disabled for 4x4 and 5x4 blocks where it nearly always slows down the
|
|
// compression and slightly reduces image quality.
|
|
|
|
float errorval_mult[2] {
|
|
1.0f / ctx.config.tune_mse_overshoot,
|
|
1.0f
|
|
};
|
|
|
|
static const float errorval_overshoot = 1.0f / ctx.config.tune_mse_overshoot;
|
|
|
|
// Only enable MODE0 fast path if enabled
|
|
// Never enable for 3D blocks as no "always" block modes are available
|
|
int start_trial = 1;
|
|
if ((ctx.config.tune_search_mode0_enable >= TUNE_MIN_SEARCH_MODE0) && (bsd.zdim == 1))
|
|
{
|
|
start_trial = 0;
|
|
}
|
|
|
|
int quant_limit = QUANT_32;
|
|
for (int i = start_trial; i < 2; i++)
|
|
{
|
|
TRACE_NODE(node1, "pass");
|
|
trace_add_data("partition_count", 1);
|
|
trace_add_data("plane_count", 1);
|
|
trace_add_data("search_mode", i);
|
|
|
|
float errorval = compress_symbolic_block_for_partition_1plane(
|
|
ctx.config, bsd, blk, i == 0,
|
|
error_threshold * errorval_mult[i] * errorval_overshoot,
|
|
1, 0, scb, tmpbuf, QUANT_32);
|
|
|
|
// Record the quant level so we can use the filter later searches
|
|
const auto& bm = bsd.get_block_mode(scb.block_mode);
|
|
quant_limit = bm.get_weight_quant_mode();
|
|
|
|
best_errorvals_for_pcount[0] = astc::min(best_errorvals_for_pcount[0], errorval);
|
|
if (errorval < (error_threshold * errorval_mult[i]))
|
|
{
|
|
trace_add_data("exit", "quality hit");
|
|
goto END_OF_TESTS;
|
|
}
|
|
}
|
|
|
|
#if !defined(ASTCENC_DIAGNOSTICS)
|
|
lowest_correl = prepare_block_statistics(bsd.texel_count, blk);
|
|
#endif
|
|
|
|
block_skip_two_plane = lowest_correl > ctx.config.tune_2plane_early_out_limit_correlation;
|
|
|
|
// Test the four possible 1-partition, 2-planes modes. Do this in reverse, as
|
|
// alpha is the most likely to be non-correlated if it is present in the data.
|
|
for (int i = BLOCK_MAX_COMPONENTS - 1; i >= 0; i--)
|
|
{
|
|
TRACE_NODE(node1, "pass");
|
|
trace_add_data("partition_count", 1);
|
|
trace_add_data("plane_count", 2);
|
|
trace_add_data("plane_component", i);
|
|
|
|
if (block_skip_two_plane)
|
|
{
|
|
trace_add_data("skip", "tune_2plane_early_out_limit_correlation");
|
|
continue;
|
|
}
|
|
|
|
if (blk.grayscale && i != 3)
|
|
{
|
|
trace_add_data("skip", "grayscale block");
|
|
continue;
|
|
}
|
|
|
|
if (blk.is_constant_channel(i))
|
|
{
|
|
trace_add_data("skip", "constant component");
|
|
continue;
|
|
}
|
|
|
|
float errorval = compress_symbolic_block_for_partition_2planes(
|
|
ctx.config, bsd, blk, error_threshold * errorval_overshoot,
|
|
i, scb, tmpbuf, quant_limit);
|
|
|
|
// If attempting two planes is much worse than the best one plane result
|
|
// then further two plane searches are unlikely to help so move on ...
|
|
if (errorval > (best_errorvals_for_pcount[0] * 1.85f))
|
|
{
|
|
break;
|
|
}
|
|
|
|
if (errorval < error_threshold)
|
|
{
|
|
trace_add_data("exit", "quality hit");
|
|
goto END_OF_TESTS;
|
|
}
|
|
}
|
|
|
|
// Find best blocks for 2, 3 and 4 partitions
|
|
for (int partition_count = 2; partition_count <= max_partitions; partition_count++)
|
|
{
|
|
unsigned int partition_indices[TUNE_MAX_PARTITIONING_CANDIDATES];
|
|
|
|
unsigned int requested_indices = requested_partition_indices[partition_count - 2];
|
|
|
|
unsigned int requested_trials = requested_partition_trials[partition_count - 2];
|
|
requested_trials = astc::min(requested_trials, requested_indices);
|
|
|
|
unsigned int actual_trials = find_best_partition_candidates(
|
|
bsd, blk, partition_count, requested_indices, partition_indices, requested_trials);
|
|
|
|
float best_error_in_prev = best_errorvals_for_pcount[partition_count - 2];
|
|
|
|
for (unsigned int i = 0; i < actual_trials; i++)
|
|
{
|
|
TRACE_NODE(node1, "pass");
|
|
trace_add_data("partition_count", partition_count);
|
|
trace_add_data("partition_index", partition_indices[i]);
|
|
trace_add_data("plane_count", 1);
|
|
trace_add_data("search_mode", i);
|
|
|
|
float errorval = compress_symbolic_block_for_partition_1plane(
|
|
ctx.config, bsd, blk, false,
|
|
error_threshold * errorval_overshoot,
|
|
partition_count, partition_indices[i],
|
|
scb, tmpbuf, quant_limit);
|
|
|
|
best_errorvals_for_pcount[partition_count - 1] = astc::min(best_errorvals_for_pcount[partition_count - 1], errorval);
|
|
|
|
// If using N partitions doesn't improve much over using N-1 partitions then skip trying
|
|
// N+1. Error can dramatically improve if the data is correlated or non-correlated and
|
|
// aligns with a partitioning that suits that encoding, so for this inner loop check add
|
|
// a large error scale because the "other" trial could be a lot better.
|
|
float best_error = best_errorvals_for_pcount[partition_count - 1];
|
|
float best_error_scale = exit_thresholds_for_pcount[partition_count - 1] * 1.85f;
|
|
if (best_error > (best_error_in_prev * best_error_scale))
|
|
{
|
|
trace_add_data("skip", "tune_partition_early_out_limit_factor");
|
|
goto END_OF_TESTS;
|
|
}
|
|
|
|
if (errorval < error_threshold)
|
|
{
|
|
trace_add_data("exit", "quality hit");
|
|
goto END_OF_TESTS;
|
|
}
|
|
}
|
|
|
|
// If using N partitions doesn't improve much over using N-1 partitions then skip trying N+1
|
|
float best_error = best_errorvals_for_pcount[partition_count - 1];
|
|
float best_error_scale = exit_thresholds_for_pcount[partition_count - 1];
|
|
if (best_error > (best_error_in_prev * best_error_scale))
|
|
{
|
|
trace_add_data("skip", "tune_partition_early_out_limit_factor");
|
|
goto END_OF_TESTS;
|
|
}
|
|
}
|
|
|
|
trace_add_data("exit", "quality not hit");
|
|
|
|
END_OF_TESTS:
|
|
// If we still have an error block then convert to something we can encode
|
|
// TODO: Do something more sensible here, such as average color block
|
|
if (scb.block_type == SYM_BTYPE_ERROR)
|
|
{
|
|
#if defined(ASTCENC_DIAGNOSTICS)
|
|
static bool printed_once = false;
|
|
if (!printed_once)
|
|
{
|
|
printed_once = true;
|
|
printf("WARN: At least one block failed to find a valid encoding.\n"
|
|
" Try increasing compression quality settings.\n\n");
|
|
}
|
|
#endif
|
|
|
|
scb.block_type = SYM_BTYPE_CONST_U16;
|
|
vfloat4 color_f32 = clamp(0.0f, 1.0f, blk.origin_texel) * 65535.0f;
|
|
vint4 color_u16 = float_to_int_rtn(color_f32);
|
|
store(color_u16, scb.constant_color);
|
|
}
|
|
|
|
// Compress to a physical block
|
|
symbolic_to_physical(bsd, scb, pcb);
|
|
}
|
|
|
|
#endif
|