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 <limits> 19 #include <random> 20 #include <vector> 21 22 #include <xnnpack.h> 23 #include <xnnpack/microfnptr.h> 24 #include <xnnpack/microparams-init.h> 25 #include <xnnpack/requantization.h> 26 27 28 class VAddMicrokernelTester { 29 public: batch_size(size_t batch_size)30 inline VAddMicrokernelTester& batch_size(size_t batch_size) { 31 assert(batch_size != 0); 32 this->batch_size_ = batch_size; 33 return *this; 34 } 35 batch_size()36 inline size_t batch_size() const { 37 return this->batch_size_; 38 } 39 inplace_a(bool inplace_a)40 inline VAddMicrokernelTester& inplace_a(bool inplace_a) { 41 this->inplace_a_ = inplace_a; 42 return *this; 43 } 44 inplace_a()45 inline bool inplace_a() const { 46 return this->inplace_a_; 47 } 48 inplace_b(bool inplace_b)49 inline VAddMicrokernelTester& inplace_b(bool inplace_b) { 50 this->inplace_b_ = inplace_b; 51 return *this; 52 } 53 inplace_b()54 inline bool inplace_b() const { 55 return this->inplace_b_; 56 } 57 a_scale(float a_scale)58 inline VAddMicrokernelTester& a_scale(float a_scale) { 59 assert(a_scale > 0.0f); 60 assert(std::isnormal(a_scale)); 61 this->a_scale_ = a_scale; 62 return *this; 63 } 64 a_scale()65 inline float a_scale() const { 66 return this->a_scale_; 67 } 68 a_zero_point(uint8_t a_zero_point)69 inline VAddMicrokernelTester& a_zero_point(uint8_t a_zero_point) { 70 this->a_zero_point_ = a_zero_point; 71 return *this; 72 } 73 a_zero_point()74 inline uint8_t a_zero_point() const { 75 return this->a_zero_point_; 76 } 77 b_scale(float b_scale)78 inline VAddMicrokernelTester& b_scale(float b_scale) { 79 assert(b_scale > 0.0f); 80 assert(std::isnormal(b_scale)); 81 this->b_scale_ = b_scale; 82 return *this; 83 } 84 b_scale()85 inline float b_scale() const { 86 return this->b_scale_; 87 } 88 b_zero_point(uint8_t b_zero_point)89 inline VAddMicrokernelTester& b_zero_point(uint8_t b_zero_point) { 90 this->b_zero_point_ = b_zero_point; 91 return *this; 92 } 93 b_zero_point()94 inline uint8_t b_zero_point() const { 95 return this->b_zero_point_; 96 } 97 y_scale(float y_scale)98 inline VAddMicrokernelTester& y_scale(float y_scale) { 99 assert(y_scale > 0.0f); 100 assert(std::isnormal(y_scale)); 101 this->y_scale_ = y_scale; 102 return *this; 103 } 104 y_scale()105 inline float y_scale() const { 106 return this->y_scale_; 107 } 108 y_zero_point(uint8_t y_zero_point)109 inline VAddMicrokernelTester& y_zero_point(uint8_t y_zero_point) { 110 this->y_zero_point_ = y_zero_point; 111 return *this; 112 } 113 y_zero_point()114 inline uint8_t y_zero_point() const { 115 return this->y_zero_point_; 116 } 117 qmin(uint8_t qmin)118 inline VAddMicrokernelTester& qmin(uint8_t qmin) { 119 this->qmin_ = qmin; 120 return *this; 121 } 122 qmin()123 inline uint8_t qmin() const { 124 return this->qmin_; 125 } 126 qmax(uint8_t qmax)127 inline VAddMicrokernelTester& qmax(uint8_t qmax) { 128 this->qmax_ = qmax; 129 return *this; 130 } 131 qmax()132 inline uint8_t qmax() const { 133 return this->qmax_; 134 } 135 iterations(size_t iterations)136 inline VAddMicrokernelTester& iterations(size_t iterations) { 137 this->iterations_ = iterations; 138 return *this; 139 } 140 iterations()141 inline size_t iterations() const { 142 return this->iterations_; 143 } 144 Test(xnn_qu8_vadd_minmax_ukernel_function vadd_minmax,xnn_init_qu8_add_minmax_params_fn init_params)145 void Test(xnn_qu8_vadd_minmax_ukernel_function vadd_minmax, xnn_init_qu8_add_minmax_params_fn init_params) const { 146 std::random_device random_device; 147 auto rng = std::mt19937(random_device()); 148 auto u8rng = std::bind(std::uniform_int_distribution<uint32_t>(0, std::numeric_limits<uint8_t>::max()), rng); 149 150 std::vector<uint8_t> a(batch_size() + XNN_EXTRA_BYTES / sizeof(uint8_t)); 151 std::vector<uint8_t> b(batch_size() + XNN_EXTRA_BYTES / sizeof(uint8_t)); 152 std::vector<uint8_t> y(batch_size() + (inplace_a() || inplace_b() ? XNN_EXTRA_BYTES / sizeof(uint8_t) : 0)); 153 std::vector<float> y_fp(batch_size()); 154 std::vector<uint8_t> y_ref(batch_size()); 155 for (size_t iteration = 0; iteration < iterations(); iteration++) { 156 std::generate(a.begin(), a.end(), std::ref(u8rng)); 157 std::generate(b.begin(), b.end(), std::ref(u8rng)); 158 if (inplace_a() || inplace_b()) { 159 std::generate(y.begin(), y.end(), std::ref(u8rng)); 160 } else { 161 std::fill(y.begin(), y.end(), 0xA5); 162 } 163 const uint8_t* a_data = inplace_a() ? y.data() : a.data(); 164 const uint8_t* b_data = inplace_b() ? y.data() : b.data(); 165 166 // Prepare parameters. 167 xnn_qu8_add_minmax_params quantization_params; 168 init_params( 169 &quantization_params, 170 a_zero_point(), b_zero_point(), y_zero_point(), 171 a_scale() / y_scale(), b_scale() / y_scale(), 172 qmin(), qmax()); 173 xnn_qu8_add_minmax_params scalar_quantization_params; 174 xnn_init_qu8_add_minmax_scalar_params( 175 &scalar_quantization_params, 176 a_zero_point(), b_zero_point(), y_zero_point(), 177 a_scale() / y_scale(), b_scale() / y_scale(), 178 qmin(), qmax()); 179 180 // Compute reference results. 181 for (size_t i = 0; i < batch_size(); i++) { 182 y_fp[i] = float(y_zero_point()) + 183 float(int32_t(a_data[i]) - int32_t(a_zero_point())) * (a_scale() / y_scale()) + 184 float(int32_t(b_data[i]) - int32_t(b_zero_point())) * (b_scale() / y_scale()); 185 y_fp[i] = std::min<float>(y_fp[i], float(qmax())); 186 y_fp[i] = std::max<float>(y_fp[i], float(qmin())); 187 y_ref[i] = xnn_qu8_quantize_add(a_data[i], b_data[i], scalar_quantization_params); 188 } 189 190 // Call optimized micro-kernel. 191 vadd_minmax(batch_size(), a_data, b_data, y.data(), &quantization_params); 192 193 // Verify results. 194 for (size_t i = 0; i < batch_size(); i++) { 195 ASSERT_LE(uint32_t(y[i]), uint32_t(qmax())) 196 << "at element " << i << " / " << batch_size(); 197 ASSERT_GE(uint32_t(y[i]), uint32_t(qmin())) 198 << "at element " << i << " / " << batch_size(); 199 ASSERT_NEAR(float(int32_t(y[i])), y_fp[i], 0.6f) 200 << "at element " << i << " / " << batch_size(); 201 ASSERT_EQ(uint32_t(y_ref[i]), uint32_t(y[i])) 202 << "at element " << i << " / " << batch_size(); 203 } 204 } 205 } 206 Test(xnn_qs8_vadd_minmax_ukernel_function vadd_minmax,xnn_init_qs8_add_minmax_params_fn init_params)207 void Test(xnn_qs8_vadd_minmax_ukernel_function vadd_minmax, xnn_init_qs8_add_minmax_params_fn init_params) const { 208 std::random_device random_device; 209 auto rng = std::mt19937(random_device()); 210 auto i8rng = std::bind( 211 std::uniform_int_distribution<int32_t>(std::numeric_limits<int8_t>::min(), std::numeric_limits<int8_t>::max()), rng); 212 213 std::vector<int8_t> a(batch_size() + XNN_EXTRA_BYTES / sizeof(int8_t)); 214 std::vector<int8_t> b(batch_size() + XNN_EXTRA_BYTES / sizeof(int8_t)); 215 std::vector<int8_t> y(batch_size() + (inplace_a() || inplace_b() ? XNN_EXTRA_BYTES / sizeof(int8_t) : 0)); 216 std::vector<float> y_fp(batch_size()); 217 std::vector<int8_t> y_ref(batch_size()); 218 for (size_t iteration = 0; iteration < iterations(); iteration++) { 219 std::generate(a.begin(), a.end(), std::ref(i8rng)); 220 std::generate(b.begin(), b.end(), std::ref(i8rng)); 221 if (inplace_a() || inplace_b()) { 222 std::generate(y.begin(), y.end(), std::ref(i8rng)); 223 } else { 224 std::fill(y.begin(), y.end(), 0xA5); 225 } 226 const int8_t* a_data = inplace_a() ? y.data() : a.data(); 227 const int8_t* b_data = inplace_b() ? y.data() : b.data(); 228 229 // Prepare parameters. 230 xnn_qs8_add_minmax_params quantization_params; 231 init_params( 232 &quantization_params, 233 int8_t(a_zero_point() - 0x80), int8_t(b_zero_point() - 0x80), int8_t(y_zero_point() - 0x80), 234 a_scale() / y_scale(), b_scale() / y_scale(), 235 int8_t(qmin() - 0x80), int8_t(qmax() - 0x80)); 236 xnn_qs8_add_minmax_params scalar_quantization_params; 237 xnn_init_qs8_add_minmax_scalar_params( 238 &scalar_quantization_params, 239 int8_t(a_zero_point() - 0x80), int8_t(b_zero_point() - 0x80), int8_t(y_zero_point() - 0x80), 240 a_scale() / y_scale(), b_scale() / y_scale(), 241 int8_t(qmin() - 0x80), int8_t(qmax() - 0x80)); 242 243 // Compute reference results. 244 for (size_t i = 0; i < batch_size(); i++) { 245 y_fp[i] = float(int32_t(y_zero_point() - 0x80)) + 246 float(int32_t(a_data[i]) - int32_t(a_zero_point() - 0x80)) * (a_scale() / y_scale()) + 247 float(int32_t(b_data[i]) - int32_t(b_zero_point() - 0x80)) * (b_scale() / y_scale()); 248 y_fp[i] = std::min<float>(y_fp[i], float(int32_t(qmax() - 0x80))); 249 y_fp[i] = std::max<float>(y_fp[i], float(int32_t(qmin() - 0x80))); 250 y_ref[i] = xnn_qs8_quantize_add(a_data[i], b_data[i], scalar_quantization_params); 251 } 252 253 // Call optimized micro-kernel. 254 vadd_minmax(batch_size(), a_data, b_data, y.data(), &quantization_params); 255 256 // Verify results. 257 for (size_t i = 0; i < batch_size(); i++) { 258 ASSERT_LE(int32_t(y[i]), int32_t(qmax() - 0x80)) 259 << "at element " << i << " / " << batch_size(); 260 ASSERT_GE(int32_t(y[i]), int32_t(qmin() - 0x80)) 261 << "at element " << i << " / " << batch_size(); 262 ASSERT_EQ(int32_t(y_ref[i]), int32_t(y[i])) 263 << "at element " << i << " / " << batch_size(); 264 ASSERT_NEAR(float(int32_t(y[i])), y_fp[i], 0.6f) 265 << "at element " << i << " / " << batch_size(); 266 } 267 } 268 } 269 270 private: 271 size_t batch_size_{1}; 272 bool inplace_a_{false}; 273 bool inplace_b_{false}; 274 float a_scale_{0.75f}; 275 float b_scale_{1.25f}; 276 float y_scale_{0.96875f}; 277 uint8_t a_zero_point_{121}; 278 uint8_t b_zero_point_{127}; 279 uint8_t y_zero_point_{133}; 280 uint8_t qmin_{0}; 281 uint8_t qmax_{255}; 282 size_t iterations_{15}; 283 }; 284