blob: a580edecb41c29b767a317a867b413019834cdf8 [file] [log] [blame]
// Copyright 2019 Google LLC
//
// This source code is licensed under the BSD-style license found in the
// LICENSE file in the root directory of this source tree.
#include <assert.h>
#include <stddef.h>
#include <psimd.h>
#include <xnnpack/common.h>
#include <xnnpack/math-stubs.h>
void xnn_math_f32_sigmoid__psimd_p5_div(
size_t n,
const float* input,
float* output)
{
assert(n % (4 * sizeof(float)) == 0);
const psimd_f32 vmagic_bias = psimd_splat_f32(0x1.8000FEp23f);
// The largest z for which sigmoidf(-z) is normalized.
// This number is also the largest z for which expf(-z) is normalized.
const psimd_f32 vdenorm_cutoff = psimd_splat_f32(0x1.5D589Ep+6f);
const psimd_f32 vminus_log2e = psimd_splat_f32(-0x1.715476p+0f);
// Last 7 bits are zeroes
const psimd_f32 vln2_hi = psimd_splat_f32(0x1.62E400p-1f);
const psimd_f32 vln2_lo = psimd_splat_f32(0x1.7F7D1Cp-20f);
const psimd_f32 vone = psimd_splat_f32(1.0f);
const psimd_f32 vc1 = psimd_splat_f32(-0x1.FFFFF6p-1f);
const psimd_f32 vc2 = psimd_splat_f32( 0x1.FFFDC6p-2f);
const psimd_f32 vc3 = psimd_splat_f32(-0x1.555A80p-3f);
const psimd_f32 vc4 = psimd_splat_f32( 0x1.573A1Ap-5f);
const psimd_f32 vc5 = psimd_splat_f32(-0x1.0F9F9Cp-7f);
for (; n != 0; n -= 4 * sizeof(float)) {
const psimd_f32 vx = psimd_load_f32(input);
input += 4;
// General structure of the algorithm:
// / exp(x) / (1 + exp(x)) if x <= 0
// f[x] :=
// \ 1 - f[-x] if x >= 0
//
// First we compute f[-z] := exp(-z) / (1 + exp(-z)) where z = abs(x),
// then replace result with 1 - f[-z] if x >= 0.
const psimd_f32 vz = psimd_abs_f32(vx);
// Compute reduced argument n := round(-z / log(2)).
// We do it by adding a large number (magic bias), which cause rounding of result to an integer, then subtracing the
// large number back. The first addition is combined with multiplication by log2e into a single FMA instruction.
// The trick with adding large number is valid only within certain bounds (|x| <= 2**22), but thats ok, because
// inputs x outside of [-87.336544, 17.328678] (i.e. z outsize [0, 87.336544]) underflow or saturate sigmoidf(x)
// anyway. We fixup the result for such inputs at the very end of the algorithm.
psimd_f32 vn = psimd_qfma_f32(vmagic_bias, vz, vminus_log2e);
// Create a floating-point number s (scale) such that s == 2**n for inputs which don't cause underflow, i.e.
// -87.336544 <= -z <= 0.0, and -126 <= n <= 0 accordingly.
const psimd_f32 vs = (psimd_f32) ((psimd_u32) vn << 23);
// Subtract the large number back to get the final n := round(-z / log(2)) as a floating-point number.
vn = psimd_sub_f32(vn, vmagic_bias);
// Compute reduced argument t := z + n * log(2). Note that -t = -z - n * log(2).
// Use Cody-Waite range reduction method (note two constants to represent log(2)) to improve accuracy.
psimd_f32 vt = psimd_qfma_f32(vz, vn, vln2_hi);
vt = psimd_qfma_f32(vt, vn, vln2_lo);
// Compute degree-5 polynomial approximation for exp(-t) on [-log(2)/2, log(2)/2]:
// P5(t) = 1 + t * (c1 + t * (c2 + t * (c3 + t * (c4 + t * c5))))
psimd_f32 vp = psimd_qfma_f32(vc4, vt, vc5);
vp = psimd_qfma_f32(vc3, vt, vp);
vp = psimd_qfma_f32(vc2, vt, vp);
vp = psimd_qfma_f32(vc1, vt, vp);
// Reconstruct the exp(-z) value:
// e = s * (1 + t * (c1 + t * (c2 + t * (c3 + t * (c4 + t * c5)))))
// = s + (t * s) * (c1 + t * (c2 + t * (c3 + t * (c4 + t * c5))))
// = s + (t * s) * p
vt = psimd_mul_f32(vt, vs);
const psimd_f32 ve = psimd_qfma_f32(vs, vt, vp);
// Reconstruct sigmoid(-z) = exp(-z) / (1.0 + exp(-z))
psimd_f32 vf = psimd_div_f32(ve, psimd_add_f32(ve, vone));
// For inputs below denormal cutoff, replace output with +0.0f.
// Note that for NaN inputs, comparison result is false, and outputs are left unchanged.
vf = psimd_andnotmask_f32(vz > vdenorm_cutoff, vf);
// Reconstruct sigmoid(x) = x < 0 ? sigmoid(-z) : 1.0 - sigmoid(-z)
vf = psimd_signblend_f32(vx, vf, psimd_sub_f32(vone, vf));
psimd_store_f32(output, vf);
output += 4;
}
}