MNN/source/backend/cpu/UnaryUtils.hpp

325 lines
8.1 KiB
C++

#ifndef UnaryUtils_hpp
#define UnaryUtils_hpp
#include <cmath>
#include <vector>
#include <limits>
template <typename Func, typename T>
static void _unaryOp(void* outputPtr, const void* inputPtr, int elementSize) {
Func f;
const T *inputData = (T*)inputPtr;
T *outputData = (T *)outputPtr;
for (int i=0; i<elementSize; ++i) {
outputData[i] = f(inputData[i]);
}
}
template <typename T>
struct UnarySquare : std::unary_function<T, T> {
T operator()(const T &x) const {
return x * x;
}
};
template <typename T>
struct UnaryRsqrt : std::unary_function<T, T> {
T operator()(const T &x) const {
return 1.f / sqrtf(x);
}
};
template <typename T>
struct UnarySqrt : std::unary_function<T, T> {
T operator()(const T &x) const {
return sqrtf(x);
}
};
template <typename T>
struct UnaryNeg {
T operator()(const T &x) const {
return -x;
}
};
template <typename T>
struct UnaryExp : std::unary_function<T, T> {
T operator()(const T &x) const {
return expf(x);
}
};
template <typename T>
struct UnaryAbs : std::unary_function<T, T> {
T operator()(const T &x) const {
return abs(x);
}
};
template <typename T>
struct UnaryCeil : std::unary_function<T, T> {
T operator()(const T &x) const {
return ceilf(x);
}
};
template <typename T>
struct UnaryRecipocal : std::unary_function<T, T> {
T operator()(const T &x) const {
return (T)1 / (x);
}
};
template <typename T>
struct UnaryLog1p : std::unary_function<T, T> {
T operator()(const T &x) const {
return (T)logf((T)1 + (x));
}
};
template <typename T>
struct UnaryLog : std::unary_function<T, T> {
T operator()(const T &x) const {
return (T)logf((T)(x));
}
};
template <typename T>
struct UnaryCos : std::unary_function<T, T> {
T operator()(const T &x) const {
return (T)cosf((T)(x));
}
};
template <typename T>
struct UnarySin : std::unary_function<T, T> {
T operator()(const T &x) const {
return (T)sinf((T)(x));
}
};
template <typename T>
struct UnaryTan : std::unary_function<T, T> {
T operator()(const T &x) const {
return (T)tanf((T)(x));
}
};
template <typename T>
struct UnaryATan : std::unary_function<T, T> {
T operator()(const T &x) const {
return (T)atanf((T)(x));
}
};
template <typename T>
struct UnaryFloor : std::unary_function<T, T> {
T operator()(const T &x) const {
return (T)floor((T)(x));
}
};
template <typename T>
struct UnarySign : std::unary_function<T, T> {
T operator()(const T &x) const {
if (x > 0) {
return 1;
}
if (x < 0) {
return -1;
}
return 0;
}
};
template <typename T>
struct UnaryBNLL : std::unary_function<T, T> {
T operator()(const T &x) const {
float r = x > 0 ? (x + log(1. + exp(-x))) : log(1. + exp(x));
return (T)r;
}
};
template <typename T>
struct UnaryAcosh : std::unary_function<T, T> {
T operator()(const T &x) const {
return (T)acoshf((T)(x));
}
};
template <typename T>
struct UnarySinh : std::unary_function<T, T> {
T operator()(const T &x) const {
return (T)sinhf((T)(x));
}
};
template <typename T>
struct UnaryAsinh : std::unary_function<T, T> {
T operator()(const T &x) const {
return (T)asinhf((T)(x));
}
};
template <typename T>
struct UnaryAtanh : std::unary_function<T, T> {
T operator()(const T &x) const {
return (T)atanhf((T)(x));
}
};
template <typename T>
struct UnaryRound : std::unary_function<T, T> {
T operator()(const T &x) const {
return (T)roundf((T)(x));
}
};
template <typename T>
struct UnaryCosh : std::unary_function<T, T> {
T operator()(const T &x) const {
return (T)coshf((T)(x));
}
};
template <typename T>
T evalPoly(T x, const std::vector<float> kErfTCoefficient) {
auto poly = 0.0f;
for (auto c : kErfTCoefficient) {
poly = poly * x + c;
}
return poly;
}
template <typename T>
T erfImpl(T x) {
// Coefficients for by erf(f32), from Cephes. tensorflow
static const std::vector<float> kErfTCoefficient {
+7.853861353153693E-5f, -8.010193625184903E-4f, +5.188327685732524E-3f,
-2.685381193529856E-2f, +1.128358514861418E-1f, -3.761262582423300E-1f,
+1.128379165726710E+0f,
};
return x * evalPoly(x * x, kErfTCoefficient);
}
template <typename T>
T erfcImpl(T x) {
// Coefficients for erfc(f32), from Cephes. tensorflow
const double kMaxlog = 88.72283905206835;
// erfc(x) = exp(-x^2) P(1/x^2), 1 < x < 2
static const std::vector<float> kErfcPCoefficient{
+2.326819970068386E-2f, -1.387039388740657E-1f, +3.687424674597105E-1f,
-5.824733027278666E-1f, +6.210004621745983E-1f, -4.944515323274145E-1f,
+3.404879937665872E-1f, -2.741127028184656E-1f, +5.638259427386472E-1f,
};
// erfc(x) = exp(-x^2) R(1/x^2), 2 <= x < kMaxlog
static const std::vector<float> kErfcRCoefficient{
-1.047766399936249E+1f, +1.297719955372516E+1f, -7.495518717768503E+0f,
+2.921019019210786E+0f, -1.015265279202700E+0f, +4.218463358204948E-1f,
-2.820767439740514E-1f, +5.641895067754075E-1f,
};
float absX = fabsf(x);
float z = expf(-x * x);
float q = 1.0 / absX;
float y = q * q;
float p;
if (absX < 2.0f) {
p = evalPoly(y, kErfcPCoefficient);
} else {
p = evalPoly(y, kErfcRCoefficient);
}
y = z * q * p;
float yClamp;
if (z < -kMaxlog) {
yClamp = 0.0f;
} else {
yClamp = y;
}
if (x < 0) {
return T(2.0f - yClamp);
} else {
return T(yClamp);
}
}
template <typename T>
struct UnaryErf : std::unary_function<T, T> {
T operator()(const T &x) const {
if (abs(x) < T(1.)) {
return erfImpl(x);
} else {
return T(1.) - erfcImpl(x);
}
}
};
template <typename T>
struct UnaryErfc : std::unary_function<T, T> {
T operator()(const T &x) const {
if (abs(x) > T(1.)) {
return erfcImpl(x);
} else {
return T(1.) - erfImpl(x);
}
}
};
template <typename T>
struct UnaryErfinv : std::unary_function<T, T> {
// referenced from tensorflow
const int kDegree = 9;
const std::vector<float> w_less_than_5_constants = {
2.81022636e-08f, 3.43273939e-07f, -3.5233877e-06f,
-4.39150654e-06f, 0.00021858087f, -0.00125372503f,
-0.00417768164f, 0.246640727f, 1.50140941f};
const std::vector<float> w_greater_than_5_constants = {
-0.000200214257f, 0.000100950558f, 0.00134934322f,
-0.00367342844f, 0.00573950773f, -0.0076224613f,
0.00943887047f, 1.00167406f, 2.83297682f};
T operator()(const T &x) const {
// Compute logarithm of (1+arg) using log1p(arg) which is more precise than
// log(1+arg) when arg is close to zero. For more details, see
// https://en.cppreference.com/w/cpp/numeric/math/log1p
auto w = -log1p(-x * x);
bool lt = (w < 5.0);
auto coefficient = [&](int i) {
if (lt) {
return w_less_than_5_constants[i];
} else {
return w_greater_than_5_constants[i];
}
};
if (lt) {
w = w - 2.5;
} else {
w = sqrt(w) - 3.0;
}
auto p = coefficient(0);
for (int i = 1; i < kDegree; i++) {
p = coefficient(i) + p * w;
}
auto result = p * x;
if (fabsf(fabsf(x) - 1) < 1e-8) {
return std::numeric_limits<float>::infinity();
} else {
return result;
}
}
};
template <typename T>
struct UnaryExpm1 : std::unary_function<T, T> {
T operator()(const T &x) const {
return (T)expm1((T)(x));
}
};
template <typename T>
struct UnaryAsin : std::unary_function<T, T> {
T operator()(const T &x) const {
return (T)asin((T)(x));
}
};
template <typename T>
struct UnaryAcos : std::unary_function<T, T> {
T operator()(const T &x) const {
return (T)acos((T)(x));
}
};
#endif