1 // Auto-generated file. Do not edit!
2 // Template: src/f32-raddstoreexpminusmax/scalar-rr2-p5.c.in
3 // Generator: tools/xngen
4 //
5 // Copyright 2020 Google LLC
6 //
7 // This source code is licensed under the BSD-style license found in the
8 // LICENSE file in the root directory of this source tree.
9
10 #include <assert.h>
11
12 #include <xnnpack/common.h>
13 #include <xnnpack/raddstoreexpminusmax.h>
14
15 #include <fp16/bitcasts.h>
16
17
xnn_f32_raddstoreexpminusmax_ukernel__scalar_rr2_p5_x2(size_t elements,const float * input,const float * max,float * output,float * sum,const union xnn_f32_expminus_params params[restrict XNN_MIN_ELEMENTS (1)])18 void xnn_f32_raddstoreexpminusmax_ukernel__scalar_rr2_p5_x2(
19 size_t elements,
20 const float* input,
21 const float* max,
22 float* output,
23 float* sum,
24 const union xnn_f32_expminus_params params[restrict XNN_MIN_ELEMENTS(1)])
25 {
26 assert(elements % sizeof(float) == 0);
27
28 const float vi_max = *max;
29 const float vlog2e = params->scalar_rr2_p5.log2e;
30 const float vmagic_bias = params->scalar_rr2_p5.magic_bias;
31 const float vminus_ln2_hi = params->scalar_rr2_p5.minus_ln2_hi;
32 const float vminus_ln2_lo = params->scalar_rr2_p5.minus_ln2_lo;
33 const float vc5 = params->scalar_rr2_p5.c5;
34 const float vc4 = params->scalar_rr2_p5.c4;
35 const float vc3 = params->scalar_rr2_p5.c3;
36 const float vc2 = params->scalar_rr2_p5.c2;
37 const float vc1 = params->scalar_rr2_p5.c1;
38 const float vdenorm_cutoff = params->scalar_rr2_p5.denorm_cutoff;
39
40 float vacc0 = 0.0f;
41 for (; elements >= 2 * sizeof(float); elements -= 2 * sizeof(float)) {
42 // Load 2 inputs at a time.
43 const float vi0 = input[0];
44 const float vi1 = input[1];
45 input += 2;
46
47 // Subtract maximum input x := i - i_max. This implies x <= 0.
48 const float vx0 = vi0 - vi_max;
49 const float vx1 = vi1 - vi_max;
50
51 // Compute reduced argument n := round(x / log(2)).
52 // We do it by adding a large number (magic bias) to the product x * (1/log(2)), which cause rounding of the result
53 // to an integer, then subtracing the large number back. The trick with adding large number is valid only within
54 // certain bounds (|x| <= 2**22), but that's ok, because inputs outside of [-87.336540, 0.0] underflow expf(x)
55 // anyway. We fixup the result for such inputs at the very end of the algorithm.
56 float vn0 = vx0 * vlog2e + vmagic_bias;
57 float vn1 = vx1 * vlog2e + vmagic_bias;
58
59 // Create a floating-point number s (scale) such that s == 2**n for inputs which don't cause underflow, i.e.
60 // -87.33642 <= x <= 0.0, and -126 <= n <= 0 accordingly.
61 const float vs0 = fp32_from_bits(fp32_to_bits(vn0) << 23);
62 const float vs1 = fp32_from_bits(fp32_to_bits(vn1) << 23);
63
64 // Subtract the large number back to get final n := round(x / log(2)).
65 vn0 -= vmagic_bias;
66 vn1 -= vmagic_bias;
67
68 // Compute reduced argument t := x - n * log(2).
69 // Use Cody-Waite range reduction method (note two constants to represent log(2)) to improve accuracy.
70 float vt0 = vn0 * vminus_ln2_hi + vx0;
71 float vt1 = vn1 * vminus_ln2_hi + vx1;
72
73 vt0 = vn0 * vminus_ln2_lo + vt0;
74 vt1 = vn1 * vminus_ln2_lo + vt1;
75
76 // Compute degree-5 polynomial approximation for exp(t) on [-log(2)/2, log(2)/2].
77 float vp0 = vc5 * vt0 + vc4;
78 float vp1 = vc5 * vt1 + vc4;
79
80 vp0 = vp0 * vt0 + vc3;
81 vp1 = vp1 * vt1 + vc3;
82
83 vp0 = vp0 * vt0 + vc2;
84 vp1 = vp1 * vt1 + vc2;
85
86 vp0 = vp0 * vt0 + vc1;
87 vp1 = vp1 * vt1 + vc1;
88
89 // Reconstruct the final f value:
90 // f = s * (1 + t * (c1 + t * (c2 + t * (c3 + t * (c4 + t * c5)))))
91 // = s + (t * s) * (c1 + t * (c2 + t * (c3 + t * (c4 + t * c5))))
92 // = s + (t * s) * p
93 vt0 *= vs0;
94 vt1 *= vs1;
95
96 float vf0 = vt0 * vp0 + vs0;
97 float vf1 = vt1 * vp1 + vs1;
98
99 // For inputs below denormal cutoff, replace output with +0.0f.
100 // Note that for NaN inputs, comparison result is false, and outputs are left unchanged.
101 if XNN_UNPREDICTABLE(vx0 < vdenorm_cutoff) {
102 vf0 = 0.0f;
103 }
104 if XNN_UNPREDICTABLE(vx1 < vdenorm_cutoff) {
105 vf1 = 0.0f;
106 }
107
108 // Store 2 outputs at a time.
109 output[0] = vf0;
110 output[1] = vf1;
111 output += 2;
112
113 // Accumulate computed exponents.
114 vacc0 += vf0;
115 vacc0 += vf1;
116 }
117
118 float vacc = vacc0;
119 for (; elements >= sizeof(float); elements -= sizeof(float)) {
120 // Load 1 input at a time.
121 const float vi = *input++;
122
123 // Subtract maximum input x := i - i_max. This implies x <= 0.
124 const float vx = vi - vi_max;
125
126 // Compute reduced argument n := round(x / log(2)).
127 // We do it by adding a large number (magic bias) to the product x * (1/log(2)), which cause rounding of the result
128 // to an integer, then subtracing the large number back. The trick with adding large number is valid only within
129 // certain bounds (|x| <= 2**22), but that's ok, because inputs outside of [-87.336540, 0.0] underflow expf(x)
130 // anyway. We fixup the result for such inputs at the very end of the algorithm.
131 float vn = vx * vlog2e + vmagic_bias;
132
133 // Create a floating-point number s (scale) such that s == 2**n for inputs which don't cause underflow, i.e.
134 // -87.33642 <= x <= 0.0, and -126 <= n <= 0 accordingly.
135 const float vs = fp32_from_bits(fp32_to_bits(vn) << 23);
136
137 // Subtract the large number back to get final n := round(x / log(2)).
138 vn -= vmagic_bias;
139
140 // Compute reduced argument t := x - n * log(2).
141 // Use Cody-Waite range reduction method (note two constants to represent log(2)) to improve accuracy.
142 float vt = vn * vminus_ln2_hi + vx;
143 vt = vn * vminus_ln2_lo + vt;
144
145 // Compute degree-5 polynomial approximation for exp(t) on [-log(2)/2, log(2)/2].
146 float vp = vc5 * vt + vc4;
147 vp = vp * vt + vc3;
148 vp = vp * vt + vc2;
149 vp = vp * vt + vc1;
150
151 // Reconstruct the final f value:
152 // f = s * (1 + t * (c1 + t * (c2 + t * (c3 + t * (c4 + t * c5)))))
153 // = s + (t * s) * (c1 + t * (c2 + t * (c3 + t * (c4 + t * c5))))
154 // = s + (t * s) * p
155 vt *= vs;
156 float vf = vt * vp + vs;
157
158 // For inputs below denormal cutoff, replace output with +0.0f.
159 // Note that for NaN inputs, comparison result is false, and outputs are left unchanged.
160 if XNN_UNPREDICTABLE(vx < vdenorm_cutoff) {
161 vf = 0.0f;
162 }
163
164 // Store 1 output at a time.
165 *output++ = vf;
166
167 // Accumulate computed exponents.
168 vacc += vf;
169 }
170 *sum = vacc;
171 }
172