1 // Copyright 2019 Google LLC 2 // 3 // This source code is licensed under the BSD-style license found in the 4 // LICENSE file in the root directory of this source tree. 5 6 #pragma once 7 8 #include <gtest/gtest.h> 9 10 #include <algorithm> 11 #include <cassert> 12 #include <cstddef> 13 #include <cstdlib> 14 #include <functional> 15 #include <random> 16 #include <vector> 17 18 #include <xnnpack.h> 19 #include <xnnpack/microfnptr.h> 20 21 22 class RAddExtExpMicrokernelTester { 23 public: elements(size_t elements)24 inline RAddExtExpMicrokernelTester& elements(size_t elements) { 25 assert(elements != 0); 26 this->elements_ = elements; 27 return *this; 28 } 29 elements()30 inline size_t elements() const { 31 return this->elements_; 32 } 33 iterations(size_t iterations)34 inline RAddExtExpMicrokernelTester& iterations(size_t iterations) { 35 this->iterations_ = iterations; 36 return *this; 37 } 38 iterations()39 inline size_t iterations() const { 40 return this->iterations_; 41 } 42 Test(xnn_f32_raddextexp_ukernel_function raddextexp)43 void Test(xnn_f32_raddextexp_ukernel_function raddextexp) const { 44 std::random_device random_device; 45 auto rng = std::mt19937(random_device()); 46 // Choose such range that expf(x[i]) overflows, but double-precision exp doesn't overflow. 47 auto f32rng = std::bind(std::uniform_real_distribution<float>(90.0f, 100.0f), rng); 48 49 std::vector<float> x(elements() + XNN_EXTRA_BYTES / sizeof(float)); 50 for (size_t iteration = 0; iteration < iterations(); iteration++) { 51 std::generate(x.begin(), x.end(), std::ref(f32rng)); 52 53 // Compute reference results. 54 double sum_ref = 0.0f; 55 for (size_t i = 0; i < elements(); i++) { 56 sum_ref += exp(double(x[i])); 57 } 58 59 // Call optimized micro-kernel. 60 float sum[2] = { nanf(""), nanf("") }; 61 raddextexp(elements() * sizeof(float), x.data(), sum); 62 63 // Verify results. 64 ASSERT_NEAR(sum_ref, exp2(double(sum[1])) * double(sum[0]), std::abs(sum_ref) * 1.0e-6) 65 << "elements = " << elements() << ", y:value = " << sum[0] << ", y:exponent = " << sum[1]; 66 } 67 } 68 69 private: 70 size_t elements_{1}; 71 size_t iterations_{15}; 72 }; 73