XNNPACK Team | b455b12 | 2019-09-27 18:10:33 -0700 | [diff] [blame] | 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 | |
Frank Barchard | a96948e | 2020-09-11 15:34:18 -0700 | [diff] [blame] | 18 | #include <fp16.h> |
| 19 | |
XNNPACK Team | b455b12 | 2019-09-27 18:10:33 -0700 | [diff] [blame] | 20 | #include <xnnpack.h> |
| 21 | |
| 22 | |
| 23 | class HardSwishOperatorTester { |
| 24 | public: |
| 25 | inline HardSwishOperatorTester& channels(size_t channels) { |
| 26 | assert(channels != 0); |
| 27 | this->channels_ = channels; |
| 28 | return *this; |
| 29 | } |
| 30 | |
| 31 | inline size_t channels() const { |
| 32 | return this->channels_; |
| 33 | } |
| 34 | |
| 35 | inline HardSwishOperatorTester& input_stride(size_t input_stride) { |
| 36 | assert(input_stride != 0); |
| 37 | this->input_stride_ = input_stride; |
| 38 | return *this; |
| 39 | } |
| 40 | |
| 41 | inline size_t input_stride() const { |
| 42 | if (this->input_stride_ == 0) { |
| 43 | return this->channels_; |
| 44 | } else { |
| 45 | assert(this->input_stride_ >= this->channels_); |
| 46 | return this->input_stride_; |
| 47 | } |
| 48 | } |
| 49 | |
| 50 | inline HardSwishOperatorTester& output_stride(size_t output_stride) { |
| 51 | assert(output_stride != 0); |
| 52 | this->output_stride_ = output_stride; |
| 53 | return *this; |
| 54 | } |
| 55 | |
| 56 | inline size_t output_stride() const { |
| 57 | if (this->output_stride_ == 0) { |
| 58 | return this->channels_; |
| 59 | } else { |
| 60 | assert(this->output_stride_ >= this->channels_); |
| 61 | return this->output_stride_; |
| 62 | } |
| 63 | } |
| 64 | |
| 65 | inline HardSwishOperatorTester& batch_size(size_t batch_size) { |
| 66 | assert(batch_size != 0); |
| 67 | this->batch_size_ = batch_size; |
| 68 | return *this; |
| 69 | } |
| 70 | |
| 71 | inline size_t batch_size() const { |
| 72 | return this->batch_size_; |
| 73 | } |
| 74 | |
| 75 | inline HardSwishOperatorTester& iterations(size_t iterations) { |
| 76 | this->iterations_ = iterations; |
| 77 | return *this; |
| 78 | } |
| 79 | |
| 80 | inline size_t iterations() const { |
| 81 | return this->iterations_; |
| 82 | } |
| 83 | |
Frank Barchard | a96948e | 2020-09-11 15:34:18 -0700 | [diff] [blame] | 84 | void TestF16() const { |
| 85 | std::random_device random_device; |
| 86 | auto rng = std::mt19937(random_device()); |
Frank Barchard | aed3278 | 2020-09-30 03:04:35 -0700 | [diff] [blame] | 87 | auto f32rng = std::bind(std::uniform_real_distribution<float>(-4.0f, 4.0f), rng); |
Frank Barchard | a96948e | 2020-09-11 15:34:18 -0700 | [diff] [blame] | 88 | auto f16rng = std::bind(fp16_ieee_from_fp32_value, f32rng); |
| 89 | |
| 90 | std::vector<uint16_t> input(XNN_EXTRA_BYTES / sizeof(uint16_t) + |
| 91 | (batch_size() - 1) * input_stride() + channels()); |
| 92 | std::vector<uint16_t> output((batch_size() - 1) * output_stride() + channels()); |
| 93 | std::vector<float> output_ref(batch_size() * channels()); |
| 94 | for (size_t iteration = 0; iteration < iterations(); iteration++) { |
| 95 | std::generate(input.begin(), input.end(), std::ref(f16rng)); |
| 96 | std::fill(output.begin(), output.end(), UINT16_C(0x7E00) /* NaN */); |
| 97 | |
| 98 | // Compute reference results. |
| 99 | for (size_t i = 0; i < batch_size(); i++) { |
| 100 | for (size_t c = 0; c < channels(); c++) { |
| 101 | const float x = fp16_ieee_to_fp32_value(input[i * input_stride() + c]); |
| 102 | const float y = x * std::min(std::max(x + 3.0f, 0.0f), 6.0f) / 6.0f; |
| 103 | output_ref[i * channels() + c] = y; |
| 104 | } |
| 105 | } |
| 106 | |
| 107 | // Create, setup, run, and destroy HardSwish operator. |
| 108 | ASSERT_EQ(xnn_status_success, xnn_initialize(nullptr /* allocator */)); |
| 109 | xnn_operator_t hardswish_op = nullptr; |
| 110 | xnn_status status = xnn_create_hardswish_nc_f16( |
| 111 | channels(), input_stride(), output_stride(), |
| 112 | 0, &hardswish_op); |
| 113 | if (status == xnn_status_unsupported_hardware) { |
| 114 | GTEST_SKIP(); |
| 115 | } |
| 116 | ASSERT_NE(nullptr, hardswish_op); |
| 117 | |
| 118 | // Smart pointer to automatically delete hardswish_op. |
| 119 | std::unique_ptr<xnn_operator, decltype(&xnn_delete_operator)> auto_hardswish_op(hardswish_op, xnn_delete_operator); |
| 120 | |
| 121 | ASSERT_EQ(xnn_status_success, |
| 122 | xnn_setup_hardswish_nc_f16( |
| 123 | hardswish_op, |
| 124 | batch_size(), |
| 125 | input.data(), output.data(), |
| 126 | nullptr /* thread pool */)); |
| 127 | |
| 128 | ASSERT_EQ(xnn_status_success, |
| 129 | xnn_run_operator(hardswish_op, nullptr /* thread pool */)); |
| 130 | |
| 131 | // Verify results. |
| 132 | for (size_t i = 0; i < batch_size(); i++) { |
| 133 | for (size_t c = 0; c < channels(); c++) { |
Frank Barchard | 7d2c1f2 | 2020-09-14 16:43:53 -0700 | [diff] [blame] | 134 | ASSERT_NEAR(fp16_ieee_to_fp32_value(output[i * output_stride() + c]), output_ref[i * channels() + c], std::max(1.0e-3f, std::abs(output_ref[i * channels() + c]) * 1.0e-2f)) |
Frank Barchard | a96948e | 2020-09-11 15:34:18 -0700 | [diff] [blame] | 135 | << "at position " << i << ", batch size = " << batch_size() << ", channels = " << channels(); |
| 136 | } |
| 137 | } |
| 138 | } |
| 139 | } |
| 140 | |
XNNPACK Team | b455b12 | 2019-09-27 18:10:33 -0700 | [diff] [blame] | 141 | void TestF32() const { |
| 142 | std::random_device random_device; |
| 143 | auto rng = std::mt19937(random_device()); |
Frank Barchard | aed3278 | 2020-09-30 03:04:35 -0700 | [diff] [blame] | 144 | auto f32rng = std::bind(std::uniform_real_distribution<float>(-4.0f, 4.0f), rng); |
XNNPACK Team | b455b12 | 2019-09-27 18:10:33 -0700 | [diff] [blame] | 145 | |
| 146 | std::vector<float> input(XNN_EXTRA_BYTES / sizeof(float) + |
| 147 | (batch_size() - 1) * input_stride() + channels()); |
| 148 | std::vector<float> output((batch_size() - 1) * output_stride() + channels()); |
| 149 | std::vector<float> output_ref(batch_size() * channels()); |
| 150 | for (size_t iteration = 0; iteration < iterations(); iteration++) { |
| 151 | std::generate(input.begin(), input.end(), std::ref(f32rng)); |
| 152 | std::fill(output.begin(), output.end(), std::nanf("")); |
| 153 | |
| 154 | // Compute reference results. |
| 155 | for (size_t i = 0; i < batch_size(); i++) { |
| 156 | for (size_t c = 0; c < channels(); c++) { |
| 157 | const float x = input[i * input_stride() + c]; |
| 158 | const float y = x * std::min(std::max(x + 3.0f, 0.0f), 6.0f) / 6.0f; |
| 159 | output_ref[i * channels() + c] = y; |
| 160 | } |
| 161 | } |
| 162 | |
| 163 | // Create, setup, run, and destroy HardSwish operator. |
Marat Dukhan | 04f03be | 2019-11-19 12:36:47 -0800 | [diff] [blame] | 164 | ASSERT_EQ(xnn_status_success, xnn_initialize(nullptr /* allocator */)); |
XNNPACK Team | b455b12 | 2019-09-27 18:10:33 -0700 | [diff] [blame] | 165 | xnn_operator_t hardswish_op = nullptr; |
| 166 | |
| 167 | ASSERT_EQ(xnn_status_success, |
| 168 | xnn_create_hardswish_nc_f32( |
| 169 | channels(), input_stride(), output_stride(), |
| 170 | 0, &hardswish_op)); |
| 171 | ASSERT_NE(nullptr, hardswish_op); |
| 172 | |
| 173 | // Smart pointer to automatically delete hardswish_op. |
| 174 | std::unique_ptr<xnn_operator, decltype(&xnn_delete_operator)> auto_hardswish_op(hardswish_op, xnn_delete_operator); |
| 175 | |
| 176 | ASSERT_EQ(xnn_status_success, |
| 177 | xnn_setup_hardswish_nc_f32( |
| 178 | hardswish_op, |
| 179 | batch_size(), |
| 180 | input.data(), output.data(), |
| 181 | nullptr /* thread pool */)); |
| 182 | |
| 183 | ASSERT_EQ(xnn_status_success, |
| 184 | xnn_run_operator(hardswish_op, nullptr /* thread pool */)); |
| 185 | |
| 186 | // Verify results. |
| 187 | for (size_t i = 0; i < batch_size(); i++) { |
| 188 | for (size_t c = 0; c < channels(); c++) { |
Frank Barchard | aed3278 | 2020-09-30 03:04:35 -0700 | [diff] [blame] | 189 | ASSERT_NEAR(output_ref[i * channels() + c], output[i * output_stride() + c], std::max(1.0e-7f, std::abs(output[i * output_stride() + c]) * 1.0e-6f)) |
XNNPACK Team | b455b12 | 2019-09-27 18:10:33 -0700 | [diff] [blame] | 190 | << "at position " << i << ", batch size = " << batch_size() << ", channels = " << channels(); |
| 191 | } |
| 192 | } |
| 193 | } |
| 194 | } |
| 195 | |
| 196 | private: |
| 197 | size_t batch_size_{1}; |
| 198 | size_t channels_{1}; |
| 199 | size_t input_stride_{0}; |
| 200 | size_t output_stride_{0}; |
| 201 | size_t iterations_{15}; |
| 202 | }; |