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/params.h> 20 #include <xnnpack/params-init.h> 21 22 23 class RAddStoreExpMinusMaxMicrokernelTester { 24 public: elements(size_t elements)25 inline RAddStoreExpMinusMaxMicrokernelTester& elements(size_t elements) { 26 assert(elements != 0); 27 this->elements_ = elements; 28 return *this; 29 } 30 elements()31 inline size_t elements() const { 32 return this->elements_; 33 } 34 iterations(size_t iterations)35 inline RAddStoreExpMinusMaxMicrokernelTester& iterations(size_t iterations) { 36 this->iterations_ = iterations; 37 return *this; 38 } 39 iterations()40 inline size_t iterations() const { 41 return this->iterations_; 42 } 43 Test(xnn_f32_raddstoreexpminusmax_ukernel_function raddstoreexpminusmax,xnn_init_f32_expminus_params_fn init_params)44 void Test(xnn_f32_raddstoreexpminusmax_ukernel_function raddstoreexpminusmax, xnn_init_f32_expminus_params_fn init_params) const { 45 std::random_device random_device; 46 auto rng = std::mt19937(random_device()); 47 // Choose such range that expf(x[i]) overflows, but expf(x[i] - x_max) doesn't. 48 // However, the range is still narrow enough that double-precision exp doesn't overflow. 49 auto f32rng = std::bind(std::uniform_real_distribution<float>(90.0f, 100.0f), rng); 50 51 std::vector<float> x(elements() + XNN_EXTRA_BYTES / sizeof(float)); 52 std::vector<float> y(elements()); 53 std::vector<double> y_ref(elements()); 54 for (size_t iteration = 0; iteration < iterations(); iteration++) { 55 std::generate(x.begin(), x.end(), std::ref(f32rng)); 56 std::fill(y.begin(), y.end(), std::nanf("")); 57 58 // Compute reference results. 59 double sum_ref = 0.0f; 60 const float x_max = *std::max_element(x.begin(), x.begin() + elements()); 61 for (size_t i = 0; i < elements(); i++) { 62 const double y_ref_value = exp(double(x[i]) - double(x_max)); 63 y_ref[i] = y_ref_value; 64 sum_ref += y_ref_value; 65 } 66 67 // Call optimized micro-kernel. 68 float sum = std::nanf(""); 69 xnn_f32_expminus_params params; 70 init_params(¶ms); 71 raddstoreexpminusmax(elements() * sizeof(float), x.data(), &x_max, y.data(), &sum, ¶ms); 72 73 // Verify results. 74 for (size_t i = 0; i < elements(); i++) { 75 ASSERT_NEAR(y_ref[i], double(y[i]), std::abs(y_ref[i]) * 1.0e-6) 76 << "i = " << i << ", elements = " << elements() << ", x_max = " << x_max; 77 } 78 ASSERT_NEAR(sum_ref, double(sum), std::abs(sum_ref) * 1.0e-6) 79 << "elements = " << elements() << ", x_max = " << x_max; 80 } 81 } 82 83 private: 84 size_t elements_{1}; 85 size_t iterations_{15}; 86 }; 87