// 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 #include #include #include #include void xnn_math_f32_expminus__scalar_rr2_p5( size_t n, const float* input, float* output) { assert(n % sizeof(float) == 0); // Large number such that ulp(magic bias) == 1 and magic bias === 127 mod 2**22. const float vmagic_bias = 0x1.8000FEp23f; const float vlog2e = 0x1.715476p+0f; // Last 7 bits are zeroes const float vminus_ln2_hi = -0x1.62E400p-1f; const float vminus_ln2_lo = -0x1.7F7D1Cp-20f; // Coefficient of polynomial approximation // exp(t) ~ 1 + t * (c1 + t * (c2 + t * (c3 + t * (c4 + t * c5)))) // on [-log(2)/2, log(2)/2] const float vc5 = 0x1.0F9F9Cp-7f; const float vc4 = 0x1.573A1Ap-5f; const float vc3 = 0x1.555A80p-3f; const float vc2 = 0x1.FFFDC6p-2f; const float vc1 = 0x1.FFFFF6p-1f; // The smallest x for which expf(x) is normalized. const float vdenorm_cutoff = -0x1.5D589Ep6f; for (; n != 0; n -= sizeof(float)) { const float vx = *input++; // Compute reduced argument n := round(x / log(2)). // We do it by adding a large number (magic bias) to the product x * (1/log(2)), which cause rounding of the result // to an integer, then subtracing the large number back. The trick with adding large number is valid only within // certain bounds (|x / log(2)| <= 2**22, i.e. |x| <= 0x1.62E43p+21 = 2907270.0), but that is acceptable, because // inputs outside of [-87.336540, 0.0] underflow expf(x) anyway. We fixup the result for such inputs at the very // end of the algorithm. float vn = vx * vlog2e + vmagic_bias; // Create a floating-point number s (scale) such that s == 2**n for inputs which don't cause underflow, i.e. // -87.33642 <= x <= 0.0, and -126 <= n <= 0 accordingly. const float vs = fp32_from_bits(fp32_to_bits(vn) << 23); // Subtract the large number back to get final n := round(x / log(2)) as a floating-point number. vn -= vmagic_bias; // Compute reduced argument t := x - n * log(2). // Use Cody-Waite range reduction method (note two constants to represent log(2)) to improve accuracy. float vt = vn * vminus_ln2_hi + vx; vt = vn * vminus_ln2_lo + vt; // Compute degree-5 polynomial approximation for exp(t) on [-log(2)/2, log(2)/2]: // P(t) = 1 + t * (c1 + t * (c2 + t * (c3 + t * (c4 + t * c5)))) = 1 + t * p float vp = vc5 * vt + vc4; vp = vp * vt + vc3; vp = vp * vt + vc2; vp = vp * vt + vc1; // Reconstruct the exp(x) value: // exp(x) = 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 *= vs; float vf = vt * vp + vs; // For inputs below denormal cutoff, replace output with +0.0f. // Note that for NaN inputs, comparison result is false, and outputs are left unchanged. if XNN_UNPREDICTABLE(vx < vdenorm_cutoff) { vf = 0.0f; } *output++ = vf; } }