// This file is part of Eigen, a lightweight C++ template library // for linear algebra. // // Copyright (C) 2014 Pedro Gonnet (pedro.gonnet@gmail.com) // Copyright (C) 2016 Gael Guennebaud <gael.guennebaud@inria.fr> // // This Source Code Form is subject to the terms of the Mozilla // Public License v. 2.0. If a copy of the MPL was not distributed // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
/** \internal \returns the hyperbolic tan of \a a (coeff-wise) Doesn't do anything fancy, just a 13/6-degree rational interpolant which is accurate up to a couple of ulps in the (approximate) range [-8, 8], outside of which tanh(x) = +/-1 in single precision. The input is clamped to the range [-c, c]. The value c is chosen as the smallest value where the approximation evaluates to exactly 1. In the reange [-0.0004, 0.0004] the approxmation tanh(x) ~= x is used for better accuracy as x tends to zero.
This implementation works on both scalars and packets.
*/ template<typename T>
T generic_fast_tanh_float(const T& a_x)
{ // Clamp the inputs to the range [-c, c] #ifdef EIGEN_VECTORIZE_FMA const T plus_clamp = pset1<T>(7.99881172180175781f); const T minus_clamp = pset1<T>(-7.99881172180175781f); #else const T plus_clamp = pset1<T>(7.90531110763549805f); const T minus_clamp = pset1<T>(-7.90531110763549805f); #endif const T tiny = pset1<T>(0.0004f); const T x = pmax(pmin(a_x, plus_clamp), minus_clamp); const T tiny_mask = pcmp_lt(pabs(a_x), tiny); // The monomial coefficients of the numerator polynomial (odd). const T alpha_1 = pset1<T>(4.89352455891786e-03f); const T alpha_3 = pset1<T>(6.37261928875436e-04f); const T alpha_5 = pset1<T>(1.48572235717979e-05f); const T alpha_7 = pset1<T>(5.12229709037114e-08f); const T alpha_9 = pset1<T>(-8.60467152213735e-11f); const T alpha_11 = pset1<T>(2.00018790482477e-13f); const T alpha_13 = pset1<T>(-2.76076847742355e-16f);
// The monomial coefficients of the denominator polynomial (even). const T beta_0 = pset1<T>(4.89352518554385e-03f); const T beta_2 = pset1<T>(2.26843463243900e-03f); const T beta_4 = pset1<T>(1.18534705686654e-04f); const T beta_6 = pset1<T>(1.19825839466702e-06f);
// Since the polynomials are odd/even, we need x^2. const T x2 = pmul(x, x);
// Evaluate the numerator polynomial p.
T p = pmadd(x2, alpha_13, alpha_11);
p = pmadd(x2, p, alpha_9);
p = pmadd(x2, p, alpha_7);
p = pmadd(x2, p, alpha_5);
p = pmadd(x2, p, alpha_3);
p = pmadd(x2, p, alpha_1);
p = pmul(x, p);
// Evaluate the denominator polynomial q.
T q = pmadd(x2, beta_6, beta_4);
q = pmadd(x2, q, beta_2);
q = pmadd(x2, q, beta_0);
// Divide the numerator by the denominator. return pselect(tiny_mask, x, pdiv(p, q));
}
template<typename RealScalar>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
RealScalar positive_real_hypot(const RealScalar& x, const RealScalar& y)
{ // IEEE IEC 6059 special cases. if ((numext::isinf)(x) || (numext::isinf)(y)) return NumTraits<RealScalar>::infinity(); if ((numext::isnan)(x) || (numext::isnan)(y)) return NumTraits<RealScalar>::quiet_NaN();
// Generic complex sqrt implementation that correctly handles corner cases // according to https://en.cppreference.com/w/cpp/numeric/complex/sqrt template<typename T>
EIGEN_DEVICE_FUNC std::complex<T> complex_sqrt(const std::complex<T>& z) { // Computes the principal sqrt of the input. // // For a complex square root of the number x + i*y. We want to find real // numbers u and v such that // (u + i*v)^2 = x + i*y <=> // u^2 - v^2 + i*2*u*v = x + i*v. // By equating the real and imaginary parts we get: // u^2 - v^2 = x // 2*u*v = y. // // For x >= 0, this has the numerically stable solution // u = sqrt(0.5 * (x + sqrt(x^2 + y^2))) // v = y / (2 * u) // and for x < 0, // v = sign(y) * sqrt(0.5 * (-x + sqrt(x^2 + y^2))) // u = y / (2 * v) // // Letting w = sqrt(0.5 * (|x| + |z|)), // if x == 0: u = w, v = sign(y) * w // if x > 0: u = w, v = y / (2 * w) // if x < 0: u = |y| / (2 * w), v = sign(y) * w
const T x = numext::real(z); const T y = numext::imag(z); const T zero = T(0); const T w = numext::sqrt(T(0.5) * (numext::abs(x) + numext::hypot(x, y)));
return
(numext::isinf)(y) ? std::complex<T>(NumTraits<T>::infinity(), y)
: x == zero ? std::complex<T>(w, y < zero ? -w : w)
: x > zero ? std::complex<T>(w, y / (2 * w))
: std::complex<T>(numext::abs(y) / (2 * w), y < zero ? -w : w );
}
// Generic complex rsqrt implementation. template<typename T>
EIGEN_DEVICE_FUNC std::complex<T> complex_rsqrt(const std::complex<T>& z) { // Computes the principal reciprocal sqrt of the input. // // For a complex reciprocal square root of the number z = x + i*y. We want to // find real numbers u and v such that // (u + i*v)^2 = 1 / (x + i*y) <=> // u^2 - v^2 + i*2*u*v = x/|z|^2 - i*v/|z|^2. // By equating the real and imaginary parts we get: // u^2 - v^2 = x/|z|^2 // 2*u*v = y/|z|^2. // // For x >= 0, this has the numerically stable solution // u = sqrt(0.5 * (x + |z|)) / |z| // v = -y / (2 * u * |z|) // and for x < 0, // v = -sign(y) * sqrt(0.5 * (-x + |z|)) / |z| // u = -y / (2 * v * |z|) // // Letting w = sqrt(0.5 * (|x| + |z|)), // if x == 0: u = w / |z|, v = -sign(y) * w / |z| // if x > 0: u = w / |z|, v = -y / (2 * w * |z|) // if x < 0: u = |y| / (2 * w * |z|), v = -sign(y) * w / |z|
const T x = numext::real(z); const T y = numext::imag(z); const T zero = T(0);
const T abs_z = numext::hypot(x, y); const T w = numext::sqrt(T(0.5) * (numext::abs(x) + abs_z)); const T woz = w / abs_z; // Corner cases consistent with 1/sqrt(z) on gcc/clang. return
abs_z == zero ? std::complex<T>(NumTraits<T>::infinity(), NumTraits<T>::quiet_NaN())
: ((numext::isinf)(x) || (numext::isinf)(y)) ? std::complex<T>(zero, zero)
: x == zero ? std::complex<T>(woz, y < zero ? woz : -woz)
: x > zero ? std::complex<T>(woz, -y / (2 * w * abs_z))
: std::complex<T>(numext::abs(y) / (2 * w * abs_z), y < zero ? woz : -woz );
}
template<typename T>
EIGEN_DEVICE_FUNC std::complex<T> complex_log(const std::complex<T>& z) { // Computes complex log.
T a = numext::abs(z);
EIGEN_USING_STD(atan2);
T b = atan2(z.imag(), z.real()); return std::complex<T>(numext::log(a), b);
}
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