XNNPACK Team | b455b12 | 2019-09-27 18:10:33 -0700 | [diff] [blame] | 1 | // Copyright (c) Facebook, Inc. and its affiliates. |
| 2 | // All rights reserved. |
| 3 | // |
| 4 | // Copyright 2019 Google LLC |
| 5 | // |
| 6 | // This source code is licensed under the BSD-style license found in the |
| 7 | // LICENSE file in the root directory of this source tree. |
| 8 | |
| 9 | #pragma once |
| 10 | |
| 11 | #include <gtest/gtest.h> |
| 12 | |
| 13 | #include <algorithm> |
| 14 | #include <cassert> |
| 15 | #include <cstddef> |
| 16 | #include <cstdlib> |
| 17 | #include <functional> |
| 18 | #include <random> |
| 19 | #include <vector> |
| 20 | |
| 21 | #include <xnnpack/params.h> |
| 22 | |
| 23 | |
| 24 | class RMaxMicrokernelTester { |
| 25 | public: |
| 26 | inline RMaxMicrokernelTester& n(size_t n) { |
| 27 | assert(n != 0); |
| 28 | this->n_ = n; |
| 29 | return *this; |
| 30 | } |
| 31 | |
| 32 | inline size_t n() const { |
| 33 | return this->n_; |
| 34 | } |
| 35 | |
| 36 | inline RMaxMicrokernelTester& iterations(size_t iterations) { |
| 37 | this->iterations_ = iterations; |
| 38 | return *this; |
| 39 | } |
| 40 | |
| 41 | inline size_t iterations() const { |
| 42 | return this->iterations_; |
| 43 | } |
| 44 | |
| 45 | void Test(xnn_u8_rmax_ukernel_function rmax) const { |
| 46 | std::random_device random_device; |
| 47 | auto rng = std::mt19937(random_device()); |
| 48 | auto u8rng = std::bind(std::uniform_int_distribution<uint8_t>(), rng); |
| 49 | |
| 50 | std::vector<uint8_t> x(n()); |
| 51 | for (size_t iteration = 0; iteration < iterations(); iteration++) { |
| 52 | std::generate(x.begin(), x.end(), std::ref(u8rng)); |
| 53 | |
| 54 | // Compute reference results. |
| 55 | uint8_t y_ref = 0; |
| 56 | for (size_t i = 0; i < n(); i++) { |
| 57 | y_ref = std::max(y_ref, x[i]); |
| 58 | } |
| 59 | |
| 60 | // Call optimized micro-kernel. |
| 61 | uint8_t y = u8rng(); |
| 62 | rmax(n() * sizeof(uint8_t), x.data(), &y); |
| 63 | |
| 64 | // Verify results. |
| 65 | ASSERT_EQ(y_ref, y) << "n = " << n(); |
| 66 | } |
| 67 | } |
| 68 | |
| 69 | void Test(xnn_f32_rmax_ukernel_function rmax) const { |
| 70 | std::random_device random_device; |
| 71 | auto rng = std::mt19937(random_device()); |
| 72 | auto f32rng = std::bind(std::uniform_real_distribution<float>(), rng); |
| 73 | |
| 74 | std::vector<float> x(n()); |
| 75 | for (size_t iteration = 0; iteration < iterations(); iteration++) { |
| 76 | std::generate(x.begin(), x.end(), std::ref(f32rng)); |
| 77 | |
| 78 | // Compute reference results. |
| 79 | float y_ref = 0; |
| 80 | for (size_t i = 0; i < n(); i++) { |
| 81 | y_ref = std::max(y_ref, x[i]); |
| 82 | } |
| 83 | |
| 84 | // Call optimized micro-kernel. |
| 85 | float y = std::nanf(""); |
| 86 | rmax(n() * sizeof(float), x.data(), &y); |
| 87 | |
| 88 | // Verify results. |
| 89 | ASSERT_EQ(y_ref, y) << "n = " << n(); |
| 90 | } |
| 91 | } |
| 92 | |
| 93 | private: |
| 94 | size_t n_{1}; |
| 95 | size_t iterations_{15}; |
| 96 | }; |