File: quant.rs

package info (click to toggle)
chromium 138.0.7204.183-1
  • links: PTS, VCS
  • area: main
  • in suites: trixie
  • size: 6,071,908 kB
  • sloc: cpp: 34,937,088; ansic: 7,176,967; javascript: 4,110,704; python: 1,419,953; asm: 946,768; xml: 739,971; pascal: 187,324; sh: 89,623; perl: 88,663; objc: 79,944; sql: 50,304; cs: 41,786; fortran: 24,137; makefile: 21,806; php: 13,980; tcl: 13,166; yacc: 8,925; ruby: 7,485; awk: 3,720; lisp: 3,096; lex: 1,327; ada: 727; jsp: 228; sed: 36
file content (236 lines) | stat: -rw-r--r-- 7,587 bytes parent folder | download | duplicates (5)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
// Copyright 2025 The Chromium Authors
// Use of this source code is governed by a BSD-style license that can be
// found in the LICENSE file.

use std::simd::prelude::*;
use std::simd::Simd;

use crate::{Reg, Reg32, UReg};

/// Subblock sums and averages, used in eval_quant_err.
#[derive(Default, Copy, Clone)]
pub struct SubblockStats {
    pub sum: [Reg; 3],
    pub avg: [Reg; 3],
}

#[inline]
pub fn fast_div_255_round(x: Reg) -> Reg {
    let r = x + Simd::splat(128);
    (r + ((r + Simd::splat(257)) >> 8)) >> 8
}

/// Compute subblock (2x4 or 4x2) sums and averages.
///
/// Returns: subblock averages in order of top, bottom, left, right.
#[inline]
pub fn prepare_averages(data: &[[[Reg; 3]; 4]; 4]) -> [SubblockStats; 4] {
    let mut sum_2x2 = [[Reg::default(); 3]; 4];
    for y in 0..2 {
        for x in 0..2 {
            for ch in 0..3 {
                sum_2x2[y * 2 + x][ch] = data[y * 2][x * 2][ch]
                    + data[y * 2 + 1][x * 2][ch]
                    + data[y * 2][x * 2 + 1][ch]
                    + data[y * 2 + 1][x * 2 + 1][ch];
            }
        }
    }
    let mut out = [SubblockStats::default(); 4];
    for (i, (s0, s1)) in [(0, 1), (2, 3), (0, 2), (1, 3)].into_iter().enumerate() {
        for ch in 0..3 {
            out[i].sum[ch] = sum_2x2[s0][ch] + sum_2x2[s1][ch];
            out[i].avg[ch] = (out[i].sum[ch] + Simd::splat(4)) >> 3;
        }
    }
    out
}

struct QuantResultWithErr {
    /// Bit 47..32 of ETC1 codeword
    lo: UReg,
    /// Bit 63..48 of ETC1 codeword
    hi: UReg,
    /// Value of endpoint 0, scaled to `0..=255``
    scaled0: [Reg; 3],
    /// Value of endpoint 1, scaled to `0..=255``
    scaled1: [Reg; 3],
    /// Error metric, see [`eval_quant_err`]
    err: Reg32,
}

pub struct QuantResult {
    /// Bit 47..32 of ETC1 codeword
    pub lo: UReg,
    /// Bit 63..48 of ETC1 codeword
    pub hi: UReg,
    /// Value of endpoint 0, scaled to `0..=255``
    pub scaled0: [Reg; 3],
    /// Value of endpoint 1, scaled to `0..=255``
    pub scaled1: [Reg; 3],
}

#[inline]
fn quant_444(
    avg0: [Reg; 3],
    avg1: [Reg; 3],
    sum0: [Reg; 3],
    sum1: [Reg; 3],
    flip: bool,
) -> QuantResultWithErr {
    #[inline]
    fn quant(avg: [Reg; 3]) -> [Reg; 3] {
        avg.map(|x| fast_div_255_round(x * Simd::splat(15)))
    }

    #[inline]
    fn scale(q: [Reg; 3]) -> [Reg; 3] {
        q.map(|x| (x << 4) | x)
    }

    #[inline]
    fn encode(q0: [Reg; 3], q1: [Reg; 3], flip: bool) -> (UReg, UReg) {
        let flip = if flip { UReg::splat(1) } else { UReg::splat(0) };
        let diff = UReg::splat(0);
        let base1_b = q1[2].cast::<u16>() << 8;
        let base0_b = q0[2].cast::<u16>() << 12;
        let lo = flip | diff | base1_b | base0_b;

        let base1_g = q1[1].cast::<u16>();
        let base0_g = q0[1].cast::<u16>() << 4;
        let base1_r = q1[0].cast::<u16>() << 8;
        let base0_r = q0[0].cast::<u16>() << 12;
        let hi = base1_g | base0_g | base1_r | base0_r;

        (lo, hi)
    }

    let q0 = quant(avg0);
    let q1 = quant(avg1);
    let scaled0 = scale(q0);
    let scaled1 = scale(q1);
    let err = eval_quant_err(scaled0, scaled1, sum0, sum1);
    let (lo, hi) = encode(q0, q1, flip);
    QuantResultWithErr { lo, hi, scaled0, scaled1, err }
}

#[inline]
fn quant_555(
    avg0: [Reg; 3],
    avg1: [Reg; 3],
    sum0: [Reg; 3],
    sum1: [Reg; 3],
    flip: bool,
) -> QuantResultWithErr {
    #[inline]
    fn quant(avg: [Reg; 3]) -> [Reg; 3] {
        avg.map(|x| fast_div_255_round(x * Simd::splat(31)))
    }
    #[inline]
    fn scale(q: [Reg; 3]) -> [Reg; 3] {
        // Per ETC1 spec, the "five-bit codewords are extended to eight bits by
        // replicating the top three highest-order bits to the three lowest
        // order bits".
        q.map(|x| (x << 3) | (x >> 2))
    }
    #[inline]
    fn encode(q0: [Reg; 3], delta: [Reg; 3], flip: bool) -> (UReg, UReg) {
        #[inline]
        fn encode_delta(d: Reg) -> UReg {
            d.cast::<u16>() & Simd::splat(0b111)
        }

        let flip = if flip { UReg::splat(1) } else { UReg::splat(0) };
        let diff = UReg::splat(1 << 1);
        let delta_b = encode_delta(delta[2]) << 8;
        let base_b = q0[2].cast::<u16>() << 11;
        let lo = flip | diff | delta_b | base_b;

        let delta_g = encode_delta(delta[1]);
        let base_g = q0[1].cast::<u16>() << 3;
        let delta_r = encode_delta(delta[0]) << 8;
        let base_r = q0[0].cast::<u16>() << 11;
        let hi = delta_g | base_g | delta_r | base_r;

        (lo, hi)
    }

    let q0 = quant(avg0);
    let q1 = quant(avg1);
    let delta = [0, 1, 2].map(|i| (q1[i] - q0[i]).simd_clamp(Simd::splat(-4), Simd::splat(3)));
    let q1 = [0, 1, 2].map(|i| q0[i] + delta[i]);

    let scaled0 = scale(q0);
    let scaled1 = scale(q1);
    let err = eval_quant_err(scaled0, scaled1, sum0, sum1);
    let (lo, hi) = encode(q0, delta, flip);
    QuantResultWithErr { lo, hi, scaled0, scaled1, err }
}

#[inline]
fn eval_quant_err(q0: [Reg; 3], q1: [Reg; 3], sum0: [Reg; 3], sum1: [Reg; 3]) -> Reg32 {
    // Target error metric:
    //   sum((x - q) ** 2)  (for each pixel)
    //   where x is the original pixel value, and
    //         q is the quantized average of the block
    // This can be rewritten as:
    //   sum(x ** 2) - 2 * sum(x * q) + sum(q ** 2)
    // For relative comparisons, sum(x ** 2) is constant and can be omitted.
    // With this and more simplification:
    //   q * sum(q - 2 * x)
    // Assuming that we are computing the sum for 8 pixels within a subblock:
    //   q * (8 * q - 2 * sum(x))
    // Dividing by 2:
    //   q * ((q << 2) - sum(x))
    (0..3).fold(Reg32::splat(0), |mut acc, i| {
        let q0 = q0[i].cast::<i32>();
        let q1 = q1[i].cast::<i32>();
        let sum0 = sum0[i].cast::<i32>();
        let sum1 = sum1[i].cast::<i32>();
        acc += q0 * ((q0 << 2) - sum0);
        acc += q1 * ((q1 << 2) - sum1);
        acc
    })
}

#[inline]
fn quantize_endpoint_pairs(
    avg0: [Reg; 3],
    avg1: [Reg; 3],
    sum0: [Reg; 3],
    sum1: [Reg; 3],
    flip: bool,
) -> QuantResultWithErr {
    let q444 = quant_444(avg0, avg1, sum0, sum1, flip);
    let q555 = quant_555(avg0, avg1, sum0, sum1, flip);

    let prefer555_32 = q555.err.simd_lt(q444.err);
    let prefer555 = prefer555_32.cast::<i16>();
    QuantResultWithErr {
        lo: prefer555.select(q555.lo, q444.lo),
        hi: prefer555.select(q555.hi, q444.hi),
        scaled0: [0, 1, 2].map(|i| prefer555.select(q555.scaled0[i], q444.scaled0[i])),
        scaled1: [0, 1, 2].map(|i| prefer555.select(q555.scaled1[i], q444.scaled1[i])),
        err: prefer555_32.select(q555.err, q444.err),
    }
}

#[inline]
/// Search through flip / no-flip and individual / differential modes, and
/// return the result with the least MSE from original pixels.
pub fn quantize_averages(data: &[[[Reg; 3]; 4]; 4]) -> QuantResult {
    let stats = prepare_averages(&data);

    let flip =
        quantize_endpoint_pairs(stats[0].avg, stats[1].avg, stats[0].sum, stats[1].sum, true);
    let no_flip =
        quantize_endpoint_pairs(stats[2].avg, stats[3].avg, stats[2].sum, stats[3].sum, false);

    let prefer_flip = flip.err.simd_lt(no_flip.err).cast::<i16>();
    QuantResult {
        lo: prefer_flip.select(flip.lo, no_flip.lo),
        hi: prefer_flip.select(flip.hi, no_flip.hi),
        scaled0: [0, 1, 2].map(|i| prefer_flip.select(flip.scaled0[i], no_flip.scaled0[i])),
        scaled1: [0, 1, 2].map(|i| prefer_flip.select(flip.scaled1[i], no_flip.scaled1[i])),
    }
}