1 // SPDX-License-Identifier: Apache-2.0
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17 
18 #if !defined(ASTCENC_DECOMPRESS_ONLY)
19 
20 /**
21  * @brief Functions for angular-sum algorithm for weight alignment.
22  *
23  * This algorithm works as follows:
24  * - we compute a complex number P as (cos s*i, sin s*i) for each weight,
25  *   where i is the input value and s is a scaling factor based on the spacing between the weights.
26  * - we then add together complex numbers for all the weights.
27  * - we then compute the length and angle of the resulting sum.
28  *
29  * This should produce the following results:
30  * - perfect alignment results in a vector whose length is equal to the sum of lengths of all inputs
31  * - even distribution results in a vector of length 0.
32  * - all samples identical results in perfect alignment for every scaling.
33  *
34  * For each scaling factor within a given set, we compute an alignment factor from 0 to 1. This
35  * should then result in some scalings standing out as having particularly good alignment factors;
36  * we can use this to produce a set of candidate scale/shift values for various quantization levels;
37  * we should then actually try them and see what happens.
38  */
39 
40 #include "astcenc_internal.h"
41 #include "astcenc_vecmathlib.h"
42 
43 #include <stdio.h>
44 #include <cassert>
45 #include <cstring>
46 
47 static constexpr unsigned int ANGULAR_STEPS { 32 };
48 
49 static_assert((ANGULAR_STEPS % ASTCENC_SIMD_WIDTH) == 0,
50               "ANGULAR_STEPS must be multiple of ASTCENC_SIMD_WIDTH");
51 
52 static_assert(ANGULAR_STEPS >= 32,
53               "ANGULAR_STEPS must be at least max(steps_for_quant_level)");
54 
55 // Store a reduced sin/cos table for 64 possible weight values; this causes
56 // slight quality loss compared to using sin() and cos() directly. Must be 2^N.
57 static constexpr unsigned int SINCOS_STEPS { 64 };
58 
59 static const uint8_t steps_for_quant_level[12] {
60 	2, 3, 4, 5, 6, 8, 10, 12, 16, 20, 24, 32
61 };
62 
63 alignas(ASTCENC_VECALIGN) static float sin_table[SINCOS_STEPS][ANGULAR_STEPS];
64 alignas(ASTCENC_VECALIGN) static float cos_table[SINCOS_STEPS][ANGULAR_STEPS];
65 
66 #if defined(ASTCENC_DIAGNOSTICS)
67 	static bool print_once { true };
68 #endif
69 
70 /* See header for documentation. */
prepare_angular_tables()71 void prepare_angular_tables()
72 {
73 	for (unsigned int i = 0; i < ANGULAR_STEPS; i++)
74 	{
75 		float angle_step = static_cast<float>(i + 1);
76 
77 		for (unsigned int j = 0; j < SINCOS_STEPS; j++)
78 		{
79 			sin_table[j][i] = static_cast<float>(sinf((2.0f * astc::PI / (SINCOS_STEPS - 1.0f)) * angle_step * static_cast<float>(j)));
80 			cos_table[j][i] = static_cast<float>(cosf((2.0f * astc::PI / (SINCOS_STEPS - 1.0f)) * angle_step * static_cast<float>(j)));
81 		}
82 	}
83 }
84 
85 /**
86  * @brief Compute the angular alignment factors and offsets.
87  *
88  * @param      weight_count              The number of (decimated) weights.
89  * @param      dec_weight_ideal_value    The ideal decimated unquantized weight values.
90  * @param      max_angular_steps         The maximum number of steps to be tested.
91  * @param[out] offsets                   The output angular offsets array.
92  */
compute_angular_offsets(unsigned int weight_count,const float * dec_weight_ideal_value,unsigned int max_angular_steps,float * offsets)93 static void compute_angular_offsets(
94 	unsigned int weight_count,
95 	const float* dec_weight_ideal_value,
96 	unsigned int max_angular_steps,
97 	float* offsets
98 ) {
99 	promise(weight_count > 0);
100 	promise(max_angular_steps > 0);
101 
102 	alignas(ASTCENC_VECALIGN) int isamplev[BLOCK_MAX_WEIGHTS];
103 
104 	// Precompute isample; arrays are always allocated 64 elements long
105 	for (unsigned int i = 0; i < weight_count; i += ASTCENC_SIMD_WIDTH)
106 	{
107 		// Add 2^23 and interpreting bits extracts round-to-nearest int
108 		vfloat sample = loada(dec_weight_ideal_value + i) * (SINCOS_STEPS - 1.0f) + vfloat(12582912.0f);
109 		vint isample = float_as_int(sample) & vint((SINCOS_STEPS - 1));
110 		storea(isample, isamplev + i);
111 	}
112 
113 	// Arrays are multiple of SIMD width (ANGULAR_STEPS), safe to overshoot max
114 	vfloat mult = vfloat(1.0f / (2.0f * astc::PI));
115 
116 	for (unsigned int i = 0; i < max_angular_steps; i += ASTCENC_SIMD_WIDTH)
117 	{
118 		vfloat anglesum_x = vfloat::zero();
119 		vfloat anglesum_y = vfloat::zero();
120 
121 		for (unsigned int j = 0; j < weight_count; j++)
122 		{
123 			int isample = isamplev[j];
124 			anglesum_x += loada(cos_table[isample] + i);
125 			anglesum_y += loada(sin_table[isample] + i);
126 		}
127 
128 		vfloat angle = atan2(anglesum_y, anglesum_x);
129 		vfloat ofs = angle * mult;
130 		storea(ofs, offsets + i);
131 	}
132 }
133 
134 /**
135  * @brief For a given step size compute the lowest and highest weight.
136  *
137  * Compute the lowest and highest weight that results from quantizing using the given stepsize and
138  * offset, and then compute the resulting error. The cut errors indicate the error that results from
139  * forcing samples that should have had one weight value one step up or down.
140  *
141  * @param      weight_count              The number of (decimated) weights.
142  * @param      dec_weight_ideal_value    The ideal decimated unquantized weight values.
143  * @param      max_angular_steps         The maximum number of steps to be tested.
144  * @param      max_quant_steps           The maximum quantization level to be tested.
145  * @param      offsets                   The angular offsets array.
146  * @param[out] lowest_weight             Per angular step, the lowest weight.
147  * @param[out] weight_span               Per angular step, the span between lowest and highest weight.
148  * @param[out] error                     Per angular step, the error.
149  * @param[out] cut_low_weight_error      Per angular step, the low weight cut error.
150  * @param[out] cut_high_weight_error     Per angular step, the high weight cut error.
151  */
compute_lowest_and_highest_weight(unsigned int weight_count,const float * dec_weight_ideal_value,unsigned int max_angular_steps,unsigned int max_quant_steps,const float * offsets,float * lowest_weight,int * weight_span,float * error,float * cut_low_weight_error,float * cut_high_weight_error)152 static void compute_lowest_and_highest_weight(
153 	unsigned int weight_count,
154 	const float* dec_weight_ideal_value,
155 	unsigned int max_angular_steps,
156 	unsigned int max_quant_steps,
157 	const float* offsets,
158 	float* lowest_weight,
159 	int* weight_span,
160 	float* error,
161 	float* cut_low_weight_error,
162 	float* cut_high_weight_error
163 ) {
164 	promise(weight_count > 0);
165 	promise(max_angular_steps > 0);
166 
167 	vfloat rcp_stepsize = vfloat::lane_id() + vfloat(1.0f);
168 
169 	// Arrays are ANGULAR_STEPS long, so always safe to run full vectors
170 	for (unsigned int sp = 0; sp < max_angular_steps; sp += ASTCENC_SIMD_WIDTH)
171 	{
172 		vfloat minidx(128.0f);
173 		vfloat maxidx(-128.0f);
174 		vfloat errval = vfloat::zero();
175 		vfloat cut_low_weight_err = vfloat::zero();
176 		vfloat cut_high_weight_err = vfloat::zero();
177 		vfloat offset = loada(offsets + sp);
178 
179 		for (unsigned int j = 0; j < weight_count; j++)
180 		{
181 			vfloat sval = load1(dec_weight_ideal_value + j) * rcp_stepsize - offset;
182 			vfloat svalrte = round(sval);
183 			vfloat diff = sval - svalrte;
184 			errval += diff * diff;
185 
186 			// Reset tracker on min hit
187 			vmask mask = svalrte < minidx;
188 			minidx = select(minidx, svalrte, mask);
189 			cut_low_weight_err = select(cut_low_weight_err, vfloat::zero(), mask);
190 
191 			// Accumulate on min hit
192 			mask = svalrte == minidx;
193 			vfloat accum = cut_low_weight_err + vfloat(1.0f) - vfloat(2.0f) * diff;
194 			cut_low_weight_err = select(cut_low_weight_err, accum, mask);
195 
196 			// Reset tracker on max hit
197 			mask = svalrte > maxidx;
198 			maxidx = select(maxidx, svalrte, mask);
199 			cut_high_weight_err = select(cut_high_weight_err, vfloat::zero(), mask);
200 
201 			// Accumulate on max hit
202 			mask = svalrte == maxidx;
203 			accum = cut_high_weight_err + vfloat(1.0f) + vfloat(2.0f) * diff;
204 			cut_high_weight_err = select(cut_high_weight_err, accum, mask);
205 		}
206 
207 		// Write out min weight and weight span; clamp span to a usable range
208 		vint span = float_to_int(maxidx - minidx + vfloat(1));
209 		span = min(span, vint(max_quant_steps + 3));
210 		span = max(span, vint(2));
211 		storea(minidx, lowest_weight + sp);
212 		storea(span, weight_span + sp);
213 
214 		// The cut_(lowest/highest)_weight_error indicate the error that results from  forcing
215 		// samples that should have had the weight value one step (up/down).
216 		vfloat ssize = 1.0f / rcp_stepsize;
217 		vfloat errscale = ssize * ssize;
218 		storea(errval * errscale, error + sp);
219 		storea(cut_low_weight_err * errscale, cut_low_weight_error + sp);
220 		storea(cut_high_weight_err * errscale, cut_high_weight_error + sp);
221 
222 		rcp_stepsize = rcp_stepsize + vfloat(ASTCENC_SIMD_WIDTH);
223 	}
224 }
225 
226 /**
227  * @brief The main function for the angular algorithm.
228  *
229  * @param      weight_count              The number of (decimated) weights.
230  * @param      dec_weight_ideal_value    The ideal decimated unquantized weight values.
231  * @param      max_quant_level           The maximum quantization level to be tested.
232  * @param[out] low_value                 Per angular step, the lowest weight value.
233  * @param[out] high_value                Per angular step, the highest weight value.
234  */
compute_angular_endpoints_for_quant_levels(unsigned int weight_count,const float * dec_weight_ideal_value,unsigned int max_quant_level,float low_value[TUNE_MAX_ANGULAR_QUANT+1],float high_value[TUNE_MAX_ANGULAR_QUANT+1])235 static void compute_angular_endpoints_for_quant_levels(
236 	unsigned int weight_count,
237 	const float* dec_weight_ideal_value,
238 	unsigned int max_quant_level,
239 	float low_value[TUNE_MAX_ANGULAR_QUANT + 1],
240 	float high_value[TUNE_MAX_ANGULAR_QUANT + 1]
241 ) {
242 	unsigned int max_quant_steps = steps_for_quant_level[max_quant_level];
243 	unsigned int max_angular_steps = steps_for_quant_level[max_quant_level];
244 
245 	alignas(ASTCENC_VECALIGN) float angular_offsets[ANGULAR_STEPS];
246 
247 	compute_angular_offsets(weight_count, dec_weight_ideal_value,
248 	                        max_angular_steps, angular_offsets);
249 
250 	alignas(ASTCENC_VECALIGN) float lowest_weight[ANGULAR_STEPS];
251 	alignas(ASTCENC_VECALIGN) int32_t weight_span[ANGULAR_STEPS];
252 	alignas(ASTCENC_VECALIGN) float error[ANGULAR_STEPS];
253 	alignas(ASTCENC_VECALIGN) float cut_low_weight_error[ANGULAR_STEPS];
254 	alignas(ASTCENC_VECALIGN) float cut_high_weight_error[ANGULAR_STEPS];
255 
256 	compute_lowest_and_highest_weight(weight_count, dec_weight_ideal_value,
257 	                                  max_angular_steps, max_quant_steps,
258 	                                  angular_offsets, lowest_weight, weight_span, error,
259 	                                  cut_low_weight_error, cut_high_weight_error);
260 
261 	// For each quantization level, find the best error terms. Use packed vectors so data-dependent
262 	// branches can become selects. This involves some integer to float casts, but the values are
263 	// small enough so they never round the wrong way.
264 	vfloat4 best_results[36];
265 
266 	// Initialize the array to some safe defaults
267 	promise(max_quant_steps > 0);
268 	for (unsigned int i = 0; i < (max_quant_steps + 4); i++)
269 	{
270 		// Lane<0> = Best error
271 		// Lane<1> = Best scale; -1 indicates no solution found
272 		// Lane<2> = Cut low weight
273 		best_results[i] = vfloat4(ERROR_CALC_DEFAULT, -1.0f, 0.0f, 0.0f);
274 	}
275 
276 	promise(max_angular_steps > 0);
277 	for (unsigned int i = 0; i < max_angular_steps; i++)
278 	{
279 		float i_flt = static_cast<float>(i);
280 
281 		int idx_span = weight_span[i];
282 
283 		float error_cut_low = error[i] + cut_low_weight_error[i];
284 		float error_cut_high = error[i] + cut_high_weight_error[i];
285 		float error_cut_low_high = error[i] + cut_low_weight_error[i] + cut_high_weight_error[i];
286 
287 		// Check best error against record N
288 		vfloat4 best_result = best_results[idx_span];
289 		vfloat4 new_result = vfloat4(error[i], i_flt, 0.0f, 0.0f);
290 		vmask4 mask = vfloat4(best_result.lane<0>()) > vfloat4(error[i]);
291 		best_results[idx_span] = select(best_result, new_result, mask);
292 
293 		// Check best error against record N-1 with either cut low or cut high
294 		best_result = best_results[idx_span - 1];
295 
296 		new_result = vfloat4(error_cut_low, i_flt, 1.0f, 0.0f);
297 		mask = vfloat4(best_result.lane<0>()) > vfloat4(error_cut_low);
298 		best_result = select(best_result, new_result, mask);
299 
300 		new_result = vfloat4(error_cut_high, i_flt, 0.0f, 0.0f);
301 		mask = vfloat4(best_result.lane<0>()) > vfloat4(error_cut_high);
302 		best_results[idx_span - 1] = select(best_result, new_result, mask);
303 
304 		// Check best error against record N-2 with both cut low and high
305 		best_result = best_results[idx_span - 2];
306 		new_result = vfloat4(error_cut_low_high, i_flt, 1.0f, 0.0f);
307 		mask = vfloat4(best_result.lane<0>()) > vfloat4(error_cut_low_high);
308 		best_results[idx_span - 2] = select(best_result, new_result, mask);
309 	}
310 
311 	for (unsigned int i = 0; i <= max_quant_level; i++)
312 	{
313 		unsigned int q = steps_for_quant_level[i];
314 		int bsi = static_cast<int>(best_results[q].lane<1>());
315 
316 		// Did we find anything?
317 #if defined(ASTCENC_DIAGNOSTICS)
318 		if ((bsi < 0) && print_once)
319 		{
320 			print_once = false;
321 			printf("INFO: Unable to find full encoding within search error limit.\n\n");
322 		}
323 #endif
324 
325 		bsi = astc::max(0, bsi);
326 
327 		float lwi = lowest_weight[bsi] + best_results[q].lane<2>();
328 		float hwi = lwi + static_cast<float>(q) - 1.0f;
329 
330 		float stepsize = 1.0f / (1.0f + static_cast<float>(bsi));
331 		low_value[i]  = (angular_offsets[bsi] + lwi) * stepsize;
332 		high_value[i] = (angular_offsets[bsi] + hwi) * stepsize;
333 	}
334 }
335 
336 /* See header for documentation. */
compute_angular_endpoints_1plane(bool only_always,const block_size_descriptor & bsd,const float * dec_weight_ideal_value,unsigned int max_weight_quant,compression_working_buffers & tmpbuf)337 void compute_angular_endpoints_1plane(
338 	bool only_always,
339 	const block_size_descriptor& bsd,
340 	const float* dec_weight_ideal_value,
341 	unsigned int max_weight_quant,
342 	compression_working_buffers& tmpbuf
343 ) {
344 	float (&low_value)[WEIGHTS_MAX_BLOCK_MODES] = tmpbuf.weight_low_value1;
345 	float (&high_value)[WEIGHTS_MAX_BLOCK_MODES] = tmpbuf.weight_high_value1;
346 
347 	float (&low_values)[WEIGHTS_MAX_DECIMATION_MODES][TUNE_MAX_ANGULAR_QUANT + 1] = tmpbuf.weight_low_values1;
348 	float (&high_values)[WEIGHTS_MAX_DECIMATION_MODES][TUNE_MAX_ANGULAR_QUANT + 1] = tmpbuf.weight_high_values1;
349 
350 	unsigned int max_decimation_modes = only_always ? bsd.decimation_mode_count_always
351 	                                                : bsd.decimation_mode_count_selected;
352 	promise(max_decimation_modes > 0);
353 	for (unsigned int i = 0; i < max_decimation_modes; i++)
354 	{
355 		const decimation_mode& dm = bsd.decimation_modes[i];
356 		if (!dm.is_ref_1_plane(static_cast<quant_method>(max_weight_quant)))
357 		{
358 			continue;
359 		}
360 
361 		unsigned int weight_count = bsd.get_decimation_info(i).weight_count;
362 
363 		unsigned int max_precision = dm.maxprec_1plane;
364 		if (max_precision > TUNE_MAX_ANGULAR_QUANT)
365 		{
366 			max_precision = TUNE_MAX_ANGULAR_QUANT;
367 		}
368 
369 		if (max_precision > max_weight_quant)
370 		{
371 			max_precision = max_weight_quant;
372 		}
373 
374 		compute_angular_endpoints_for_quant_levels(
375 		    weight_count,
376 		    dec_weight_ideal_value + i * BLOCK_MAX_WEIGHTS,
377 		    max_precision, low_values[i], high_values[i]);
378 	}
379 
380 	unsigned int max_block_modes = only_always ? bsd.block_mode_count_1plane_always
381 	                                           : bsd.block_mode_count_1plane_selected;
382 	promise(max_block_modes > 0);
383 	for (unsigned int i = 0; i < max_block_modes; i++)
384 	{
385 		const block_mode& bm = bsd.block_modes[i];
386 		assert(!bm.is_dual_plane);
387 
388 		unsigned int quant_mode = bm.quant_mode;
389 		unsigned int decim_mode = bm.decimation_mode;
390 
391 		if (quant_mode <= TUNE_MAX_ANGULAR_QUANT)
392 		{
393 			low_value[i] = low_values[decim_mode][quant_mode];
394 			high_value[i] = high_values[decim_mode][quant_mode];
395 		}
396 		else
397 		{
398 			low_value[i] = 0.0f;
399 			high_value[i] = 1.0f;
400 		}
401 	}
402 }
403 
404 /* See header for documentation. */
compute_angular_endpoints_2planes(const block_size_descriptor & bsd,const float * dec_weight_ideal_value,unsigned int max_weight_quant,compression_working_buffers & tmpbuf)405 void compute_angular_endpoints_2planes(
406 	const block_size_descriptor& bsd,
407 	const float* dec_weight_ideal_value,
408 	unsigned int max_weight_quant,
409 	compression_working_buffers& tmpbuf
410 ) {
411 	float (&low_value1)[WEIGHTS_MAX_BLOCK_MODES] = tmpbuf.weight_low_value1;
412 	float (&high_value1)[WEIGHTS_MAX_BLOCK_MODES] = tmpbuf.weight_high_value1;
413 	float (&low_value2)[WEIGHTS_MAX_BLOCK_MODES] = tmpbuf.weight_low_value2;
414 	float (&high_value2)[WEIGHTS_MAX_BLOCK_MODES] = tmpbuf.weight_high_value2;
415 
416 	float (&low_values1)[WEIGHTS_MAX_DECIMATION_MODES][TUNE_MAX_ANGULAR_QUANT + 1] = tmpbuf.weight_low_values1;
417 	float (&high_values1)[WEIGHTS_MAX_DECIMATION_MODES][TUNE_MAX_ANGULAR_QUANT + 1] = tmpbuf.weight_high_values1;
418 	float (&low_values2)[WEIGHTS_MAX_DECIMATION_MODES][TUNE_MAX_ANGULAR_QUANT + 1] = tmpbuf.weight_low_values2;
419 	float (&high_values2)[WEIGHTS_MAX_DECIMATION_MODES][TUNE_MAX_ANGULAR_QUANT + 1] = tmpbuf.weight_high_values2;
420 
421 	promise(bsd.decimation_mode_count_selected > 0);
422 	for (unsigned int i = 0; i < bsd.decimation_mode_count_selected; i++)
423 	{
424 		const decimation_mode& dm = bsd.decimation_modes[i];
425 		if (!dm.is_ref_2_plane(static_cast<quant_method>(max_weight_quant)))
426 		{
427 			continue;
428 		}
429 
430 		unsigned int weight_count = bsd.get_decimation_info(i).weight_count;
431 
432 		unsigned int max_precision = dm.maxprec_2planes;
433 		if (max_precision > TUNE_MAX_ANGULAR_QUANT)
434 		{
435 			max_precision = TUNE_MAX_ANGULAR_QUANT;
436 		}
437 
438 		if (max_precision > max_weight_quant)
439 		{
440 			max_precision = max_weight_quant;
441 		}
442 
443 		compute_angular_endpoints_for_quant_levels(
444 		    weight_count,
445 		    dec_weight_ideal_value + i * BLOCK_MAX_WEIGHTS,
446 		    max_precision, low_values1[i], high_values1[i]);
447 
448 		compute_angular_endpoints_for_quant_levels(
449 		    weight_count,
450 		    dec_weight_ideal_value + i * BLOCK_MAX_WEIGHTS + WEIGHTS_PLANE2_OFFSET,
451 		    max_precision, low_values2[i], high_values2[i]);
452 	}
453 
454 	unsigned int start = bsd.block_mode_count_1plane_selected;
455 	unsigned int end = bsd.block_mode_count_1plane_2plane_selected;
456 	for (unsigned int i = start; i < end; i++)
457 	{
458 		const block_mode& bm = bsd.block_modes[i];
459 		unsigned int quant_mode = bm.quant_mode;
460 		unsigned int decim_mode = bm.decimation_mode;
461 
462 		if (quant_mode <= TUNE_MAX_ANGULAR_QUANT)
463 		{
464 			low_value1[i] = low_values1[decim_mode][quant_mode];
465 			high_value1[i] = high_values1[decim_mode][quant_mode];
466 			low_value2[i] = low_values2[decim_mode][quant_mode];
467 			high_value2[i] = high_values2[decim_mode][quant_mode];
468 		}
469 		else
470 		{
471 			low_value1[i] = 0.0f;
472 			high_value1[i] = 1.0f;
473 			low_value2[i] = 0.0f;
474 			high_value2[i] = 1.0f;
475 		}
476 	}
477 }
478 
479 #endif
480