| // 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 <arm_neon.h> |
| |
| #include <xnnpack/math-stubs.h> |
| |
| |
| void xnn_math_f32_sigmoid__neonfma_rr1_p5_nr1recps1fma( |
| size_t n, |
| const float* input, |
| float* output) |
| { |
| assert(n % (4 * sizeof(float)) == 0); |
| |
| const float32x4_t vmagic_bias = vmovq_n_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 float32x4_t vdenorm_cutoff = vmovq_n_f32(-0x1.5D589Ep+6f); |
| const float32x4_t vminus_log2e = vmovq_n_f32(-0x1.715476p+0f); |
| const float32x4_t vln2 = vmovq_n_f32(0x1.62E43p-1f); |
| const float32x4_t vone = vmovq_n_f32(1.0f); |
| |
| const float32x4_t vc1 = vmovq_n_f32(-0x1.FFFFF6p-1f); |
| const float32x4_t vc2 = vmovq_n_f32(0x1.FFFDC6p-2f); |
| const float32x4_t vc3 = vmovq_n_f32(-0x1.555A80p-3f); |
| const float32x4_t vc4 = vmovq_n_f32(0x1.573A1Ap-5f); |
| const float32x4_t vc5 = vmovq_n_f32(-0x1.0F9F9Cp-7f); |
| |
| for (; n != 0; n -= 4 * sizeof(float)) { |
| const float32x4_t vx = vld1q_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 float32x4_t vz = vabsq_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. |
| float32x4_t vn = vfmaq_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 float32x4_t vs = vreinterpretq_f32_s32(vshlq_n_s32(vreinterpretq_s32_f32(vn), 23)); |
| |
| // Subtract the large number back to get the final n := round(-z / log(2)) as a floating-point number. |
| vn = vsubq_f32(vn, vmagic_bias); |
| |
| // Compute reduced argument t := z + n * log(2). Note that -t = -z - n * log(2). |
| float32x4_t vt = vfmaq_f32(vz, vn, vln2); |
| |
| // 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)))) |
| float32x4_t vp = vfmaq_f32(vc4, vc5, vt); |
| vp = vfmaq_f32(vc3, vp, vt); |
| vp = vfmaq_f32(vc2, vp, vt); |
| vp = vfmaq_f32(vc1, vp, vt); |
| |
| // 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 = vmulq_f32(vt, vs); |
| float32x4_t ve = vfmaq_f32(vs, vp, vt); |
| |
| // Denominator of the sigmoid fraction: 1.0 + exp(-z) |
| float32x4_t vd = vaddq_f32(ve, vone); |
| |
| // Use Newton-Raphson method (2 iterations) to compute reciprocal of denominator. |
| // Note: 1 < d <= 2, because z >= 0.0 and 0 < exp(-z) <= 1.0. |
| // Thus the reciprocal of the denominator never overflows. |
| float32x4_t vr = vrecpeq_f32(vd); |
| vr = vmulq_f32(vr, vrecpsq_f32(vr, vd)); |
| vr = vfmaq_f32(vr, vr, vfmsq_f32(vone, vr, vd)); |
| |
| // Reconstruct sigmoid(-z) = exp(-z) / (1.0 + exp(-z)) |
| float32x4_t vf = vmulq_f32(ve, vr); |
| |
| // 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 = vreinterpretq_f32_u32(vbicq_u32(vreinterpretq_u32_f32(vf), vcagtq_f32(vx, vdenorm_cutoff))); |
| |
| // Reconstruct sigmoid(x) = x < 0 ? sigmoid(-z) : 1.0 - sigmoid(-z) |
| const uint32x4_t vm = vcltq_f32(vx, vmovq_n_f32(0.0f)); |
| vf = vbslq_f32(vm, vf, vsubq_f32(vone, vf)); |
| |
| vst1q_f32(output, vf); output += 4; |
| } |
| } |