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1// Copyright 2019 Google LLC
2//
3// This source code is licensed under the BSD-style license found in the
4// LICENSE file in the root directory of this source tree.
5
6$assert BATCH_TILE >= 1
7$ABC = "0123456789ABCDEFGHIJKLMNOPQRSTUVWXYZ"
8#include <assert.h>
9#include <math.h>
10
11#include <xnnpack/common.h>
12#include <xnnpack/math.h>
13#include <xnnpack/vunary.h>
14
15
16void xnn_f32_vsigmoid_ukernel__scalar_rr2_p5_div_x${BATCH_TILE}(
17    size_t n,
18    const float* x,
19    float* y,
20    const union xnn_f32_sigmoid_params params[restrict XNN_MIN_ELEMENTS(1)])
21{
22  assert(n % sizeof(float) == 0);
23
24  const float vmagic_bias = params->scalar_rr2_p5.magic_bias;
25  const float vminus_log2e = params->scalar_rr2_p5.minus_log2e;
26  const float vln2_hi = params->scalar_rr2_p5.ln2_hi;
27  const float vln2_lo = params->scalar_rr2_p5.ln2_lo;
28  const float vc5 = params->scalar_rr2_p5.c5;
29  const float vc4 = params->scalar_rr2_p5.c4;
30  const float vc3 = params->scalar_rr2_p5.c3;
31  const float vc2 = params->scalar_rr2_p5.c2;
32  const float vc1 = params->scalar_rr2_p5.c1;
33  const float vone = params->scalar_rr2_p5.one;
34  const float vdenorm_cutoff = params->scalar_rr2_p5.denorm_cutoff;
35
36  $if BATCH_TILE > 1:
37    for (; n >= ${BATCH_TILE} * sizeof(float); n -= ${BATCH_TILE} * sizeof(float)) {
38      $for N in range(BATCH_TILE):
39        const float vx${N} = x[${N}];
40      x += ${BATCH_TILE};
41
42      $for N in range(BATCH_TILE):
43        const float vz${N} = fabsf(vx${N});
44
45      $for N in range(BATCH_TILE):
46        float vn${N} = vz${N} * vminus_log2e + vmagic_bias;
47
48      $for N in range(BATCH_TILE):
49        const float vs${N} = uint32_as_float(float_as_uint32(vn${N}) << 23);
50
51      $for N in range(BATCH_TILE):
52        vn${N} -= vmagic_bias;
53
54      $for N in range(BATCH_TILE):
55        float vt${N} = vn${N} * vln2_hi + vz${N};
56
57      $for N in range(BATCH_TILE):
58        vt${N} = vn${N} * vln2_lo + vt${N};
59
60      $for N in range(BATCH_TILE):
61        float vp${N} = vt${N} * vc5 + vc4;
62
63      $for N in range(BATCH_TILE):
64        vp${N} = vt${N} * vp${N} + vc3;
65
66      $for N in range(BATCH_TILE):
67        vp${N} = vt${N} * vp${N} + vc2;
68
69      $for N in range(BATCH_TILE):
70        vp${N} = vt${N} * vp${N} + vc1;
71
72      $for N in range(BATCH_TILE):
73        vt${N} *= vs${N};
74
75      $for N in range(BATCH_TILE):
76        const float ve${N} = vt${N} * vp${N} + vs${N};
77
78      $for N in range(BATCH_TILE):
79        const float vd${N} = ve${N} + vone;
80
81      $for N in range(BATCH_TILE):
82        float vf${N} = ve${N} / vd${N};
83
84      $for N in range(BATCH_TILE):
85        if XNN_UNPREDICTABLE(vz${N} > vdenorm_cutoff) {
86          vf${N} = 0.0f;
87        }
88
89      $for N in range(BATCH_TILE):
90        if XNN_UNPREDICTABLE(vx${N} > 0.0f) {
91          vf${N} = vone - vf${N};
92        }
93
94      $for N in range(BATCH_TILE):
95        y[${N}] = vf${N};
96      y += ${BATCH_TILE};
97    }
98  $if BATCH_TILE == 1:
99    do {
100      const float vx = *x++;
101
102      const float vz = fabsf(vx);
103
104      float vn = vz * vminus_log2e + vmagic_bias;
105      const float vs = uint32_as_float(float_as_uint32(vn) << 23);
106      vn -= vmagic_bias;
107
108      float vt = vn * vln2_hi + vz;
109      vt = vn * vln2_lo + vt;
110
111      float vp = vt * vc5 + vc4;
112      vp = vt * vp + vc3;
113      vp = vt * vp + vc2;
114      vp = vt * vp + vc1;
115
116      vt *= vs;
117      const float ve = vt * vp + vs;
118      const float vd = ve + vone;
119
120      float vf = ve / vd;
121      if XNN_UNPREDICTABLE(vz > vdenorm_cutoff) {
122        vf = 0.0f;
123      }
124      if XNN_UNPREDICTABLE(vx > 0.0f) {
125        vf = vone - vf;
126      }
127
128      *y++ = vf;
129
130      n -= sizeof(float);
131    } while (n != 0);
132  $elif BATCH_TILE == 2:
133    if XNN_UNLIKELY(n != 0) {
134      const float vx = *x;
135
136      const float vz = fabsf(vx);
137
138      float vn = vz * vminus_log2e + vmagic_bias;
139      const float vs = uint32_as_float(float_as_uint32(vn) << 23);
140      vn -= vmagic_bias;
141
142      float vt = vn * vln2_hi + vz;
143      vt = vn * vln2_lo + vt;
144
145      float vp = vt * vc5 + vc4;
146      vp = vt * vp + vc3;
147      vp = vt * vp + vc2;
148      vp = vt * vp + vc1;
149
150      vt *= vs;
151      const float ve = vt * vp + vs;
152      const float vd = ve + vone;
153
154      float vf = ve / vd;
155      if XNN_UNPREDICTABLE(vz > vdenorm_cutoff) {
156        vf = 0.0f;
157      }
158      if XNN_UNPREDICTABLE(vx > 0.0f) {
159        vf = vone - vf;
160      }
161
162      *y = vf;
163    }
164  $else:
165    if XNN_UNLIKELY(n != 0) {
166      do {
167        const float vx = *x++;
168
169        const float vz = fabsf(vx);
170
171        float vn = vz * vminus_log2e + vmagic_bias;
172        const float vs = uint32_as_float(float_as_uint32(vn) << 23);
173        vn -= vmagic_bias;
174
175        float vt = vn * vln2_hi + vz;
176        vt = vn * vln2_lo + vt;
177
178        float vp = vt * vc5 + vc4;
179        vp = vt * vp + vc3;
180        vp = vt * vp + vc2;
181        vp = vt * vp + vc1;
182
183        vt *= vs;
184        const float ve = vt * vp + vs;
185        const float vd = ve + vone;
186
187        float vf = ve / vd;
188        if XNN_UNPREDICTABLE(vz > vdenorm_cutoff) {
189          vf = 0.0f;
190        }
191        if XNN_UNPREDICTABLE(vx > 0.0f) {
192          vf = vone - vf;
193        }
194
195        *y++ = vf;
196
197        n -= sizeof(float);
198      } while (n != 0);
199    }
200}
201