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#include <algorithm> #include <fstream> #include <iostream> #include <math.h> #include <random> #include <cstdio> #include <ctime> #include <vector> struct ufunc { std::string name; double (f32func)(double); long double (f64func)(long double); float f32ulp; float f64ulp; }; template <typename T> T RandomFloat(T a, T b) { T random = ((T)rand()) / (T)RAND_MAX; T diff = b - a; T r = random * diff; return a + r; } template <typename T> void append_random_array(std::vector<T> &arr, T min, T max, size_t N) { for (size_t ii = 0; ii < N; ++ii) arr.emplace_back(RandomFloat<T>(min, max)); } template <typename T1, typename T2> std::vector<T1> computeTrueVal(const std::vector<T1> &in, T2 (mathfunc)(T2)) { std::vector<T1> out; for (T1 elem : in) { T2 elem_d = (T2)elem; T1 out_elem = (T1)mathfunc(elem_d); out.emplace_back(out_elem); } return out; } / * FP range: * [-inf, -maxflt, -1., -minflt, -minden, 0., minden, minflt, 1., maxflt, inf] / #define MINDEN std::numeric_limits<T>::denorm_min() #define MINFLT std::numeric_limits<T>::min() #define MAXFLT std::numeric_limits<T>::max() #define INF std::numeric_limits<T>::infinity() #define qNAN std::numeric_limits<T>::quiet_NaN() #define sNAN std::numeric_limits<T>::signaling_NaN() template <typename T> std::vector<T> generate_input_vector(std::string func) { std::vector<T> input = {MINDEN, -MINDEN, MINFLT, -MINFLT, MAXFLT, -MAXFLT, INF, -INF, qNAN, sNAN, -1.0, 1.0, 0.0, -0.0}; // [-1.0, 1.0] if ((func == "arcsin") \|\| (func == "arccos") \|\| (func == "arctanh")) { append_random_array<T>(input, -1.0, 1.0, 700); } // (0.0, INF] else if ((func == "log2") \|\| (func == "log10")) { append_random_array<T>(input, 0.0, 1.0, 200); append_random_array<T>(input, MINDEN, MINFLT, 200); append_random_array<T>(input, MINFLT, 1.0, 200); append_random_array<T>(input, 1.0, MAXFLT, 200); } // (-1.0, INF] else if (func == "log1p") { append_random_array<T>(input, -1.0, 1.0, 200); append_random_array<T>(input, -MINFLT, -MINDEN, 100); append_random_array<T>(input, -1.0, -MINFLT, 100); append_random_array<T>(input, MINDEN, MINFLT, 100); append_random_array<T>(input, MINFLT, 1.0, 100); append_random_array<T>(input, 1.0, MAXFLT, 100); } // [1.0, INF] else if (func == "arccosh") { append_random_array<T>(input, 1.0, 2.0, 400); append_random_array<T>(input, 2.0, MAXFLT, 300); } // [-INF, INF] else { append_random_array<T>(input, -1.0, 1.0, 100); append_random_array<T>(input, MINDEN, MINFLT, 100); append_random_array<T>(input, -MINFLT, -MINDEN, 100); append_random_array<T>(input, MINFLT, 1.0, 100); append_random_array<T>(input, -1.0, -MINFLT, 100); append_random_array<T>(input, 1.0, MAXFLT, 100); append_random_array<T>(input, -MAXFLT, -100.0, 100); } std::random_shuffle(input.begin(), input.end()); return input; } int main() { srand(42); std::vector<struct ufunc> umathfunc = { {"sin", sin, sin, 1.49, 1.00}, {"cos", cos, cos, 1.49, 1.00}, {"tan", tan, tan, 3.91, 3.93}, {"arcsin", asin, asin, 3.12, 2.55}, {"arccos", acos, acos, 2.1, 1.67}, {"arctan", atan, atan, 2.3, 2.52}, {"sinh", sinh, sinh, 1.55, 1.89}, {"cosh", cosh, cosh, 2.48, 1.97}, {"tanh", tanh, tanh, 1.38, 1.19}, {"arcsinh", asinh, asinh, 1.01, 1.48}, {"arccosh", acosh, acosh, 1.16, 1.05}, {"arctanh", atanh, atanh, 1.45, 1.46}, {"cbrt", cbrt, cbrt, 1.94, 1.82}, //{"exp",exp,exp,3.76,1.53}, {"exp2", exp2, exp2, 1.01, 1.04}, {"expm1", expm1, expm1, 2.62, 2.1}, //{"log",log,log,1.84,1.67}, {"log10", log10, log10, 3.5, 1.92}, {"log1p", log1p, log1p, 1.96, 1.93}, {"log2", log2, log2, 2.12, 1.84}, }; for (int ii = 0; ii < umathfunc.size(); ++ii) { // ignore sin/cos if ((umathfunc[ii].name != "sin") && (umathfunc[ii].name != "cos")) { std::string fileName = "umath-validation-set-" + umathfunc[ii].name + ".csv"; std::ofstream txtOut; txtOut.open(fileName, std::ofstream::trunc); txtOut << "dtype,input,output,ulperrortol" << std::endl; // Single Precision auto f32in = generate_input_vector<float>(umathfunc[ii].name); auto f32out = computeTrueVal<float, double>(f32in, umathfunc[ii].f32func); for (int jj = 0; jj < f32in.size(); ++jj) { txtOut << "np.float32" << std::hex << ",0x" << reinterpret_cast<uint32_t >(&f32in[jj]) << ",0x" << reinterpret_cast<uint32_t >(&f32out[jj]) << "," << ceil(umathfunc[ii].f32ulp) << std::endl; } // Double Precision auto f64in = generate_input_vector<double>(umathfunc[ii].name); auto f64out = computeTrueVal<double, long double>( f64in, umathfunc[ii].f64func); for (int jj = 0; jj < f64in.size(); ++jj) { txtOut << "np.float64" << std::hex << ",0x" << reinterpret_cast<uint64_t >(&f64in[jj]) << ",0x" << reinterpret_cast<uint64_t *>(&f64out[jj]) << "," << ceil(umathfunc[ii].f64ulp) << std::endl; } txtOut.close(); } } return 0; }