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 <cmath> |
| 16 | #include <cstddef> |
| 17 | #include <cstdlib> |
| 18 | #include <functional> |
Marat Dukhan | 5ce30d9 | 2020-04-14 03:31:26 -0700 | [diff] [blame] | 19 | #include <limits> |
XNNPACK Team | b455b12 | 2019-09-27 18:10:33 -0700 | [diff] [blame] | 20 | #include <random> |
| 21 | #include <vector> |
| 22 | |
| 23 | #include <xnnpack.h> |
| 24 | |
| 25 | |
| 26 | class LeakyReLUOperatorTester { |
| 27 | public: |
| 28 | inline LeakyReLUOperatorTester& channels(size_t channels) { |
| 29 | assert(channels != 0); |
| 30 | this->channels_ = channels; |
| 31 | return *this; |
| 32 | } |
| 33 | |
| 34 | inline size_t channels() const { |
| 35 | return this->channels_; |
| 36 | } |
| 37 | |
| 38 | inline LeakyReLUOperatorTester& input_stride(size_t input_stride) { |
| 39 | assert(input_stride != 0); |
| 40 | this->input_stride_ = input_stride; |
| 41 | return *this; |
| 42 | } |
| 43 | |
| 44 | inline size_t input_stride() const { |
| 45 | if (this->input_stride_ == 0) { |
| 46 | return this->channels_; |
| 47 | } else { |
| 48 | assert(this->input_stride_ >= this->channels_); |
| 49 | return this->input_stride_; |
| 50 | } |
| 51 | } |
| 52 | |
| 53 | inline LeakyReLUOperatorTester& output_stride(size_t output_stride) { |
| 54 | assert(output_stride != 0); |
| 55 | this->output_stride_ = output_stride; |
| 56 | return *this; |
| 57 | } |
| 58 | |
| 59 | inline size_t output_stride() const { |
| 60 | if (this->output_stride_ == 0) { |
| 61 | return this->channels_; |
| 62 | } else { |
| 63 | assert(this->output_stride_ >= this->channels_); |
| 64 | return this->output_stride_; |
| 65 | } |
| 66 | } |
| 67 | |
| 68 | inline LeakyReLUOperatorTester& batch_size(size_t batch_size) { |
| 69 | assert(batch_size != 0); |
| 70 | this->batch_size_ = batch_size; |
| 71 | return *this; |
| 72 | } |
| 73 | |
| 74 | inline size_t batch_size() const { |
| 75 | return this->batch_size_; |
| 76 | } |
| 77 | |
| 78 | inline LeakyReLUOperatorTester& negative_slope(float negative_slope) { |
| 79 | assert(negative_slope > 0.0f); |
| 80 | assert(negative_slope < 1.0f); |
| 81 | this->negative_slope_ = negative_slope; |
| 82 | return *this; |
| 83 | } |
| 84 | |
| 85 | inline float negative_slope() const { |
| 86 | return this->negative_slope_; |
| 87 | } |
| 88 | |
| 89 | inline LeakyReLUOperatorTester& input_scale(float input_scale) { |
| 90 | assert(input_scale > 0.0f); |
| 91 | assert(std::isnormal(input_scale)); |
| 92 | this->input_scale_ = input_scale; |
| 93 | return *this; |
| 94 | } |
| 95 | |
| 96 | inline float input_scale() const { |
| 97 | return this->input_scale_; |
| 98 | } |
| 99 | |
| 100 | inline LeakyReLUOperatorTester& input_zero_point(uint8_t input_zero_point) { |
| 101 | this->input_zero_point_ = input_zero_point; |
| 102 | return *this; |
| 103 | } |
| 104 | |
| 105 | inline uint8_t input_zero_point() const { |
| 106 | return this->input_zero_point_; |
| 107 | } |
| 108 | |
| 109 | inline LeakyReLUOperatorTester& output_scale(float output_scale) { |
| 110 | assert(output_scale > 0.0f); |
| 111 | assert(std::isnormal(output_scale)); |
| 112 | this->output_scale_ = output_scale; |
| 113 | return *this; |
| 114 | } |
| 115 | |
| 116 | inline float output_scale() const { |
| 117 | return this->output_scale_; |
| 118 | } |
| 119 | |
| 120 | inline LeakyReLUOperatorTester& output_zero_point(uint8_t output_zero_point) { |
| 121 | this->output_zero_point_ = output_zero_point; |
| 122 | return *this; |
| 123 | } |
| 124 | |
| 125 | inline uint8_t output_zero_point() const { |
| 126 | return this->output_zero_point_; |
| 127 | } |
| 128 | |
| 129 | inline LeakyReLUOperatorTester& qmin(uint8_t qmin) { |
| 130 | this->qmin_ = qmin; |
| 131 | return *this; |
| 132 | } |
| 133 | |
| 134 | inline uint8_t qmin() const { |
| 135 | return this->qmin_; |
| 136 | } |
| 137 | |
| 138 | inline LeakyReLUOperatorTester& qmax(uint8_t qmax) { |
| 139 | this->qmax_ = qmax; |
| 140 | return *this; |
| 141 | } |
| 142 | |
| 143 | inline uint8_t qmax() const { |
| 144 | return this->qmax_; |
| 145 | } |
| 146 | |
| 147 | inline LeakyReLUOperatorTester& iterations(size_t iterations) { |
| 148 | this->iterations_ = iterations; |
| 149 | return *this; |
| 150 | } |
| 151 | |
| 152 | inline size_t iterations() const { |
| 153 | return this->iterations_; |
| 154 | } |
| 155 | |
Marat Dukhan | 2881333 | 2020-06-10 18:05:38 -0700 | [diff] [blame] | 156 | void TestF32() const { |
| 157 | std::random_device random_device; |
| 158 | auto rng = std::mt19937(random_device()); |
| 159 | auto f32rng = std::bind(std::uniform_real_distribution<float>(-1.0f, 1.0f), std::ref(rng)); |
| 160 | |
| 161 | std::vector<float> input(XNN_EXTRA_BYTES / sizeof(float) + (batch_size() - 1) * input_stride() + channels()); |
| 162 | std::vector<float> output((batch_size() - 1) * output_stride() + channels()); |
| 163 | std::vector<float> output_ref(batch_size() * channels()); |
| 164 | for (size_t iteration = 0; iteration < iterations(); iteration++) { |
| 165 | std::generate(input.begin(), input.end(), std::ref(f32rng)); |
| 166 | std::fill(output.begin(), output.end(), std::nanf("")); |
| 167 | |
| 168 | // Compute reference results. |
| 169 | for (size_t i = 0; i < batch_size(); i++) { |
| 170 | for (size_t c = 0; c < channels(); c++) { |
| 171 | const float x = input[i * input_stride() + c]; |
| 172 | const float y = std::signbit(x) ? x * negative_slope() : x; |
| 173 | output_ref[i * channels() + c] = y; |
| 174 | } |
| 175 | } |
| 176 | |
| 177 | // Create, setup, run, and destroy Leaky ReLU operator. |
| 178 | ASSERT_EQ(xnn_status_success, xnn_initialize(nullptr /* allocator */)); |
| 179 | xnn_operator_t leaky_relu_op = nullptr; |
| 180 | |
| 181 | ASSERT_EQ(xnn_status_success, |
| 182 | xnn_create_leaky_relu_nc_f32( |
| 183 | channels(), input_stride(), output_stride(), |
| 184 | negative_slope(), |
| 185 | 0, &leaky_relu_op)); |
| 186 | ASSERT_NE(nullptr, leaky_relu_op); |
| 187 | |
| 188 | // Smart pointer to automatically delete leaky_relu_op. |
| 189 | std::unique_ptr<xnn_operator, decltype(&xnn_delete_operator)> auto_leaky_relu_op(leaky_relu_op, xnn_delete_operator); |
| 190 | |
| 191 | ASSERT_EQ(xnn_status_success, |
| 192 | xnn_setup_leaky_relu_nc_f32( |
| 193 | leaky_relu_op, |
| 194 | batch_size(), |
| 195 | input.data(), output.data(), |
| 196 | nullptr /* thread pool */)); |
| 197 | |
| 198 | ASSERT_EQ(xnn_status_success, |
| 199 | xnn_run_operator(leaky_relu_op, nullptr /* thread pool */)); |
| 200 | |
| 201 | // Verify results. |
| 202 | for (size_t i = 0; i < batch_size(); i++) { |
| 203 | for (size_t c = 0; c < channels(); c++) { |
| 204 | ASSERT_EQ(output[i * output_stride() + c], output_ref[i * channels() + c]) |
| 205 | << "at batch " << i << " / " << batch_size() << ", channel " << c << " / " << channels() |
| 206 | << ", input " << input[i * input_stride() + c] << ", negative slope " << negative_slope(); |
| 207 | } |
| 208 | } |
| 209 | } |
| 210 | } |
| 211 | |
Marat Dukhan | 08b7a97 | 2020-07-14 18:17:29 -0700 | [diff] [blame] | 212 | void TestQU8() const { |
XNNPACK Team | b455b12 | 2019-09-27 18:10:33 -0700 | [diff] [blame] | 213 | std::random_device random_device; |
| 214 | auto rng = std::mt19937(random_device()); |
Marat Dukhan | 5ce30d9 | 2020-04-14 03:31:26 -0700 | [diff] [blame] | 215 | auto u8rng = std::bind(std::uniform_int_distribution<uint32_t>(0, std::numeric_limits<uint8_t>::max()), rng); |
XNNPACK Team | b455b12 | 2019-09-27 18:10:33 -0700 | [diff] [blame] | 216 | |
Marat Dukhan | aea2d55 | 2021-09-17 11:15:59 -0700 | [diff] [blame] | 217 | std::vector<uint8_t> input(XNN_EXTRA_BYTES / sizeof(uint8_t) + (batch_size() - 1) * input_stride() + channels()); |
XNNPACK Team | b455b12 | 2019-09-27 18:10:33 -0700 | [diff] [blame] | 218 | std::vector<uint8_t> output((batch_size() - 1) * output_stride() + channels()); |
| 219 | std::vector<float> output_ref(batch_size() * channels()); |
| 220 | for (size_t iteration = 0; iteration < iterations(); iteration++) { |
| 221 | std::generate(input.begin(), input.end(), std::ref(u8rng)); |
| 222 | std::fill(output.begin(), output.end(), 0xA5); |
| 223 | |
| 224 | // Compute reference results. |
| 225 | for (size_t i = 0; i < batch_size(); i++) { |
| 226 | for (size_t c = 0; c < channels(); c++) { |
| 227 | const float x = input_scale() * (int32_t(input[i * input_stride() + c]) - int32_t(input_zero_point())); |
| 228 | float y = (x < 0.0f ? x * negative_slope() : x) / output_scale(); |
| 229 | y = std::min<float>(y, int32_t(qmax()) - int32_t(output_zero_point())); |
| 230 | y = std::max<float>(y, int32_t(qmin()) - int32_t(output_zero_point())); |
| 231 | output_ref[i * channels() + c] = y + float(int32_t(output_zero_point())); |
| 232 | } |
| 233 | } |
| 234 | |
Marat Dukhan | 2881333 | 2020-06-10 18:05:38 -0700 | [diff] [blame] | 235 | // Create, setup, run, and destroy Leaky ReLU operator. |
Marat Dukhan | 04f03be | 2019-11-19 12:36:47 -0800 | [diff] [blame] | 236 | ASSERT_EQ(xnn_status_success, xnn_initialize(nullptr /* allocator */)); |
XNNPACK Team | b455b12 | 2019-09-27 18:10:33 -0700 | [diff] [blame] | 237 | xnn_operator_t leaky_relu_op = nullptr; |
| 238 | |
| 239 | ASSERT_EQ(xnn_status_success, |
Marat Dukhan | 08b7a97 | 2020-07-14 18:17:29 -0700 | [diff] [blame] | 240 | xnn_create_leaky_relu_nc_qu8( |
XNNPACK Team | b455b12 | 2019-09-27 18:10:33 -0700 | [diff] [blame] | 241 | channels(), input_stride(), output_stride(), |
| 242 | negative_slope(), |
| 243 | input_zero_point(), input_scale(), |
| 244 | output_zero_point(), output_scale(), |
| 245 | qmin(), qmax(), |
| 246 | 0, &leaky_relu_op)); |
| 247 | ASSERT_NE(nullptr, leaky_relu_op); |
| 248 | |
| 249 | // Smart pointer to automatically delete leaky_relu_op. |
| 250 | std::unique_ptr<xnn_operator, decltype(&xnn_delete_operator)> auto_leaky_relu_op(leaky_relu_op, xnn_delete_operator); |
| 251 | |
| 252 | ASSERT_EQ(xnn_status_success, |
Marat Dukhan | 08b7a97 | 2020-07-14 18:17:29 -0700 | [diff] [blame] | 253 | xnn_setup_leaky_relu_nc_qu8( |
XNNPACK Team | b455b12 | 2019-09-27 18:10:33 -0700 | [diff] [blame] | 254 | leaky_relu_op, |
| 255 | batch_size(), |
| 256 | input.data(), output.data(), |
| 257 | nullptr /* thread pool */)); |
| 258 | |
| 259 | ASSERT_EQ(xnn_status_success, |
| 260 | xnn_run_operator(leaky_relu_op, nullptr /* thread pool */)); |
| 261 | |
| 262 | // Verify results. |
| 263 | for (size_t i = 0; i < batch_size(); i++) { |
| 264 | for (size_t c = 0; c < channels(); c++) { |
| 265 | ASSERT_NEAR(float(int32_t(output[i * output_stride() + c])), output_ref[i * channels() + c], 0.6f); |
| 266 | } |
| 267 | } |
| 268 | } |
| 269 | } |
| 270 | |
| 271 | private: |
| 272 | size_t batch_size_{1}; |
| 273 | size_t channels_{1}; |
| 274 | size_t input_stride_{0}; |
| 275 | size_t output_stride_{0}; |
| 276 | float negative_slope_{0.5f}; |
| 277 | float output_scale_{0.75f}; |
| 278 | uint8_t output_zero_point_{133}; |
| 279 | float input_scale_{1.25f}; |
| 280 | uint8_t input_zero_point_{121}; |
| 281 | uint8_t qmin_{0}; |
| 282 | uint8_t qmax_{255}; |
| 283 | size_t iterations_{15}; |
| 284 | }; |