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 <limits> |
| 16 | #include <random> |
| 17 | #include <vector> |
| 18 | |
| 19 | #include <xnnpack.h> |
| 20 | |
| 21 | |
| 22 | class UnpoolingOperatorTester { |
| 23 | public: |
| 24 | inline UnpoolingOperatorTester& padding(uint32_t padding) { |
| 25 | this->padding_top_ = padding; |
| 26 | this->padding_right_ = padding; |
| 27 | this->padding_bottom_ = padding; |
| 28 | this->padding_left_ = padding; |
| 29 | return *this; |
| 30 | } |
| 31 | |
| 32 | inline UnpoolingOperatorTester& padding(uint32_t padding_height, uint32_t padding_width) { |
| 33 | this->padding_top_ = padding_height; |
| 34 | this->padding_right_ = padding_width; |
| 35 | this->padding_bottom_ = padding_height; |
| 36 | this->padding_left_ = padding_width; |
| 37 | return *this; |
| 38 | } |
| 39 | |
| 40 | inline UnpoolingOperatorTester& padding_height(uint32_t padding_height) { |
| 41 | this->padding_top_ = padding_height; |
| 42 | this->padding_bottom_ = padding_height; |
| 43 | return *this; |
| 44 | } |
| 45 | |
| 46 | inline UnpoolingOperatorTester& padding_width(uint32_t padding_width) { |
| 47 | this->padding_right_ = padding_width; |
| 48 | this->padding_left_ = padding_width; |
| 49 | return *this; |
| 50 | } |
| 51 | |
| 52 | inline UnpoolingOperatorTester& padding_top(uint32_t padding_top) { |
| 53 | this->padding_top_ = padding_top; |
| 54 | return *this; |
| 55 | } |
| 56 | |
| 57 | inline uint32_t padding_top() const { |
| 58 | return this->padding_top_; |
| 59 | } |
| 60 | |
| 61 | inline UnpoolingOperatorTester& padding_right(uint32_t padding_right) { |
| 62 | this->padding_right_ = padding_right; |
| 63 | return *this; |
| 64 | } |
| 65 | |
| 66 | inline uint32_t padding_right() const { |
| 67 | return this->padding_right_; |
| 68 | } |
| 69 | |
| 70 | inline UnpoolingOperatorTester& padding_bottom(uint32_t padding_bottom) { |
| 71 | this->padding_bottom_ = padding_bottom; |
| 72 | return *this; |
| 73 | } |
| 74 | |
| 75 | inline uint32_t padding_bottom() const { |
| 76 | return this->padding_bottom_; |
| 77 | } |
| 78 | |
| 79 | inline UnpoolingOperatorTester& padding_left(uint32_t padding_left) { |
| 80 | this->padding_left_ = padding_left; |
| 81 | return *this; |
| 82 | } |
| 83 | |
| 84 | inline uint32_t padding_left() const { |
| 85 | return this->padding_left_; |
| 86 | } |
| 87 | |
| 88 | inline UnpoolingOperatorTester& input_size(size_t input_height, size_t input_width) { |
| 89 | assert(input_height >= 1); |
| 90 | assert(input_width >= 1); |
| 91 | this->input_height_ = input_height; |
| 92 | this->input_width_ = input_width; |
| 93 | return *this; |
| 94 | } |
| 95 | |
| 96 | inline UnpoolingOperatorTester& input_height(size_t input_height) { |
| 97 | assert(input_height >= 1); |
| 98 | this->input_height_ = input_height; |
| 99 | return *this; |
| 100 | } |
| 101 | |
| 102 | inline size_t input_height() const { |
| 103 | return this->input_height_; |
| 104 | } |
| 105 | |
| 106 | inline UnpoolingOperatorTester& input_width(size_t input_width) { |
| 107 | assert(input_width >= 1); |
| 108 | this->input_width_ = input_width; |
| 109 | return *this; |
| 110 | } |
| 111 | |
| 112 | inline size_t input_width() const { |
| 113 | return this->input_width_; |
| 114 | } |
| 115 | |
| 116 | inline UnpoolingOperatorTester& channels(size_t channels) { |
| 117 | assert(channels != 0); |
| 118 | this->channels_ = channels; |
| 119 | return *this; |
| 120 | } |
| 121 | |
| 122 | inline size_t channels() const { |
| 123 | return this->channels_; |
| 124 | } |
| 125 | |
| 126 | inline UnpoolingOperatorTester& batch_size(size_t batch_size) { |
| 127 | assert(batch_size != 0); |
| 128 | this->batch_size_ = batch_size; |
| 129 | return *this; |
| 130 | } |
| 131 | |
| 132 | inline size_t batch_size() const { |
| 133 | return this->batch_size_; |
| 134 | } |
| 135 | |
| 136 | inline UnpoolingOperatorTester& pooling_size(uint32_t pooling_size) { |
| 137 | assert(pooling_size >= 1); |
| 138 | this->pooling_height_ = pooling_size; |
| 139 | this->pooling_width_ = pooling_size; |
| 140 | return *this; |
| 141 | } |
| 142 | |
| 143 | inline UnpoolingOperatorTester& pooling_size(uint32_t pooling_height, uint32_t pooling_width) { |
| 144 | assert(pooling_height >= 1); |
| 145 | assert(pooling_width >= 1); |
| 146 | this->pooling_height_ = pooling_height; |
| 147 | this->pooling_width_ = pooling_width; |
| 148 | return *this; |
| 149 | } |
| 150 | |
| 151 | inline UnpoolingOperatorTester& pooling_height(uint32_t pooling_height) { |
| 152 | assert(pooling_height >= 1); |
| 153 | this->pooling_height_ = pooling_height; |
| 154 | return *this; |
| 155 | } |
| 156 | |
| 157 | inline uint32_t pooling_height() const { |
| 158 | return this->pooling_height_; |
| 159 | } |
| 160 | |
| 161 | inline UnpoolingOperatorTester& pooling_width(uint32_t pooling_width) { |
| 162 | assert(pooling_width >= 1); |
| 163 | this->pooling_width_ = pooling_width; |
| 164 | return *this; |
| 165 | } |
| 166 | |
| 167 | inline uint32_t pooling_width() const { |
| 168 | return this->pooling_width_; |
| 169 | } |
| 170 | |
| 171 | inline size_t output_height() const { |
| 172 | const size_t padding_height = padding_top() + padding_bottom(); |
| 173 | return std::max<size_t>(input_height() * pooling_height(), padding_height) - padding_height; |
| 174 | } |
| 175 | |
| 176 | inline size_t output_width() const { |
| 177 | const size_t padding_width = padding_left() + padding_right(); |
| 178 | return std::max<size_t>(input_width() * pooling_width(), padding_width) - padding_width; |
| 179 | } |
| 180 | |
| 181 | inline UnpoolingOperatorTester& input_pixel_stride(size_t input_pixel_stride) { |
| 182 | assert(input_pixel_stride != 0); |
| 183 | this->input_pixel_stride_ = input_pixel_stride; |
| 184 | return *this; |
| 185 | } |
| 186 | |
| 187 | inline size_t input_pixel_stride() const { |
| 188 | if (this->input_pixel_stride_ == 0) { |
| 189 | return channels(); |
| 190 | } else { |
| 191 | assert(this->input_pixel_stride_ >= channels()); |
| 192 | return this->input_pixel_stride_; |
| 193 | } |
| 194 | } |
| 195 | |
| 196 | inline UnpoolingOperatorTester& output_pixel_stride(size_t output_pixel_stride) { |
| 197 | assert(output_pixel_stride != 0); |
| 198 | this->output_pixel_stride_ = output_pixel_stride; |
| 199 | return *this; |
| 200 | } |
| 201 | |
| 202 | inline size_t output_pixel_stride() const { |
| 203 | if (this->output_pixel_stride_ == 0) { |
| 204 | return channels(); |
| 205 | } else { |
| 206 | assert(this->output_pixel_stride_ >= channels()); |
| 207 | return this->output_pixel_stride_; |
| 208 | } |
| 209 | } |
| 210 | |
| 211 | inline UnpoolingOperatorTester& next_input_size(uint32_t next_input_height, uint32_t next_input_width) { |
| 212 | assert(next_input_height >= 1); |
| 213 | assert(next_input_width >= 1); |
| 214 | this->next_input_height_ = next_input_height; |
| 215 | this->next_input_width_ = next_input_width; |
| 216 | return *this; |
| 217 | } |
| 218 | |
| 219 | inline UnpoolingOperatorTester& next_input_height(uint32_t next_input_height) { |
| 220 | assert(next_input_height >= 1); |
| 221 | this->next_input_height_ = next_input_height; |
| 222 | return *this; |
| 223 | } |
| 224 | |
| 225 | inline uint32_t next_input_height() const { |
| 226 | if (this->next_input_height_ == 0) { |
| 227 | return input_height(); |
| 228 | } else { |
| 229 | return this->next_input_height_; |
| 230 | } |
| 231 | } |
| 232 | |
| 233 | inline UnpoolingOperatorTester& next_input_width(uint32_t next_input_width) { |
| 234 | assert(next_input_width >= 1); |
| 235 | this->next_input_width_ = next_input_width; |
| 236 | return *this; |
| 237 | } |
| 238 | |
| 239 | inline uint32_t next_input_width() const { |
| 240 | if (this->next_input_width_ == 0) { |
| 241 | return input_width(); |
| 242 | } else { |
| 243 | return this->next_input_width_; |
| 244 | } |
| 245 | } |
| 246 | |
| 247 | inline size_t next_output_height() const { |
| 248 | const size_t padding_height = padding_top() + padding_bottom(); |
| 249 | return std::max<size_t>(next_input_height() * pooling_height(), padding_height) - padding_height; |
| 250 | } |
| 251 | |
| 252 | inline size_t next_output_width() const { |
| 253 | const size_t padding_width = padding_left() + padding_right(); |
| 254 | return std::max<size_t>(next_input_width() * pooling_width(), padding_width) - padding_width; |
| 255 | } |
| 256 | |
| 257 | inline UnpoolingOperatorTester& next_batch_size(size_t next_batch_size) { |
| 258 | assert(next_batch_size >= 1); |
| 259 | this->next_batch_size_ = next_batch_size; |
| 260 | return *this; |
| 261 | } |
| 262 | |
| 263 | inline size_t next_batch_size() const { |
| 264 | if (this->next_batch_size_ == 0) { |
| 265 | return batch_size(); |
| 266 | } else { |
| 267 | return this->next_batch_size_; |
| 268 | } |
| 269 | } |
| 270 | |
| 271 | inline UnpoolingOperatorTester& iterations(size_t iterations) { |
| 272 | this->iterations_ = iterations; |
| 273 | return *this; |
| 274 | } |
| 275 | |
| 276 | inline size_t iterations() const { |
| 277 | return this->iterations_; |
| 278 | } |
| 279 | |
| 280 | void TestX32() const { |
| 281 | std::random_device random_device; |
| 282 | auto rng = std::mt19937(random_device()); |
| 283 | auto u32rng = std::bind(std::uniform_int_distribution<uint32_t>(), std::ref(rng)); |
| 284 | auto idx_rng = std::bind(std::uniform_int_distribution<uint32_t>(0, pooling_height() * pooling_width() - 1), std::ref(rng)); |
| 285 | |
| 286 | std::vector<uint32_t> input((batch_size() * input_height() * input_width() - 1) * input_pixel_stride() + channels()); |
| 287 | std::vector<uint32_t> index(batch_size() * input_height() * input_width() * channels()); |
| 288 | std::vector<uint32_t> output((batch_size() * output_height() * output_width() - 1) * output_pixel_stride() + channels()); |
| 289 | std::vector<uint32_t> output_ref(batch_size() * output_height() * output_width() * channels()); |
| 290 | for (size_t iteration = 0; iteration < iterations(); iteration++) { |
| 291 | std::generate(input.begin(), input.end(), std::ref(u32rng)); |
| 292 | std::generate(index.begin(), index.end(), std::ref(idx_rng)); |
| 293 | std::generate(output.begin(), output.end(), std::ref(u32rng)); |
| 294 | |
| 295 | // Compute reference results. |
| 296 | std::fill(output_ref.begin(), output_ref.end(), 0); |
| 297 | for (size_t i = 0; i < batch_size(); i++) { |
| 298 | for (size_t iy = 0; iy < input_height(); iy++) { |
| 299 | for (size_t ix = 0; ix < input_width(); ix++) { |
| 300 | for (size_t c = 0; c < channels(); c++) { |
| 301 | const uint32_t pooling_index = index[((i * input_height() + iy) * input_width() + ix) * channels() + c]; |
| 302 | const uint32_t py = pooling_index % pooling_height(); |
| 303 | const uint32_t px = pooling_index / pooling_height(); |
| 304 | const size_t oy = std::min(std::max<size_t>(iy * pooling_height() + py, padding_top()) - padding_top(), output_height() - 1); |
| 305 | const size_t ox = std::min(std::max<size_t>(ix * pooling_width() + px, padding_left()) - padding_left(), output_width() - 1); |
| 306 | output_ref[((i * output_height() + oy) * output_width() + ox) * channels() + c] = |
| 307 | input[((i * input_height() + iy) * input_width() + ix) * input_pixel_stride() + c]; |
| 308 | } |
| 309 | } |
| 310 | } |
| 311 | } |
| 312 | |
| 313 | // Create, setup, run, and destroy Unpooling operator. |
Marat Dukhan | 04f03be | 2019-11-19 12:36:47 -0800 | [diff] [blame] | 314 | ASSERT_EQ(xnn_status_success, xnn_initialize(nullptr /* allocator */)); |
XNNPACK Team | b455b12 | 2019-09-27 18:10:33 -0700 | [diff] [blame] | 315 | xnn_operator_t unpooling_op = nullptr; |
| 316 | |
| 317 | ASSERT_EQ(xnn_status_success, |
| 318 | xnn_create_unpooling2d_nhwc_x32( |
| 319 | padding_top(), padding_right(), padding_bottom(), padding_left(), |
| 320 | pooling_height(), pooling_width(), |
| 321 | channels(), input_pixel_stride(), output_pixel_stride(), |
| 322 | 0, &unpooling_op)); |
| 323 | ASSERT_NE(nullptr, unpooling_op); |
| 324 | |
| 325 | // Smart pointer to automatically delete unpooling_op. |
| 326 | std::unique_ptr<xnn_operator, decltype(&xnn_delete_operator)> auto_unpooling_op(unpooling_op, xnn_delete_operator); |
| 327 | |
| 328 | ASSERT_EQ(xnn_status_success, |
| 329 | xnn_setup_unpooling2d_nhwc_x32( |
| 330 | unpooling_op, |
| 331 | batch_size(), input_height(), input_width(), |
| 332 | input.data(), index.data(), output.data(), |
| 333 | nullptr /* thread pool */)); |
| 334 | |
| 335 | ASSERT_EQ(xnn_status_success, |
| 336 | xnn_run_operator(unpooling_op, nullptr /* thread pool */)); |
| 337 | |
| 338 | // Verify results. |
| 339 | for (size_t i = 0; i < batch_size(); i++) { |
| 340 | for (size_t c = 0; c < channels(); c++) { |
| 341 | for (size_t y = 0; y < output_height(); y++) { |
| 342 | for (size_t x = 0; x < output_width(); x++) { |
| 343 | EXPECT_EQ(output_ref[((i * output_height() + y) * output_width() + x) * channels() + c], |
| 344 | output[((i * output_height() + y) * output_width() + x) * output_pixel_stride() + c]) << |
| 345 | "in batch index " << i << ", pixel (" << y << ", " << x << "), channel " << c; |
| 346 | } |
| 347 | } |
| 348 | } |
| 349 | } |
| 350 | } |
| 351 | } |
| 352 | |
| 353 | void TestSetupX32() const { |
| 354 | std::random_device random_device; |
| 355 | auto rng = std::mt19937(random_device()); |
| 356 | auto u32rng = std::bind(std::uniform_int_distribution<uint32_t>(), std::ref(rng)); |
| 357 | auto idx_rng = std::bind(std::uniform_int_distribution<uint32_t>(0, pooling_height() * pooling_width() - 1), std::ref(rng)); |
| 358 | |
| 359 | std::vector<uint32_t> input(std::max( |
| 360 | (batch_size() * input_height() * input_width() - 1) * input_pixel_stride() + channels(), |
| 361 | (next_batch_size() * next_input_height() * next_input_width() - 1) * input_pixel_stride() + channels())); |
| 362 | std::vector<uint32_t> index(std::max( |
| 363 | batch_size() * input_height() * input_width() * channels(), |
| 364 | next_batch_size() * next_input_height() * next_input_width() * channels())); |
| 365 | std::vector<uint32_t> output(std::max( |
| 366 | (batch_size() * output_height() * output_width() - 1) * output_pixel_stride() + channels(), |
| 367 | (next_batch_size() * next_output_height() * next_output_width() - 1) * output_pixel_stride() * channels())); |
| 368 | std::vector<uint32_t> output_ref(batch_size() * output_height() * output_width() * channels()); |
| 369 | std::vector<uint32_t> next_output_ref(next_batch_size() * next_output_height() * next_output_width() * channels()); |
| 370 | |
| 371 | for (size_t iteration = 0; iteration < iterations(); iteration++) { |
| 372 | std::generate(input.begin(), input.end(), std::ref(u32rng)); |
| 373 | std::generate(index.begin(), index.end(), std::ref(idx_rng)); |
| 374 | std::generate(output.begin(), output.end(), std::ref(u32rng)); |
| 375 | |
| 376 | // Compute reference results. |
| 377 | std::fill(output_ref.begin(), output_ref.end(), 0); |
| 378 | for (size_t i = 0; i < batch_size(); i++) { |
| 379 | for (size_t iy = 0; iy < input_height(); iy++) { |
| 380 | for (size_t ix = 0; ix < input_width(); ix++) { |
| 381 | for (size_t c = 0; c < channels(); c++) { |
| 382 | const uint32_t pooling_index = index[((i * input_height() + iy) * input_width() + ix) * channels() + c]; |
| 383 | const uint32_t py = pooling_index % pooling_height(); |
| 384 | const uint32_t px = pooling_index / pooling_height(); |
| 385 | const size_t oy = std::min(std::max<size_t>(iy * pooling_height() + py, padding_top()) - padding_top(), output_height() - 1); |
| 386 | const size_t ox = std::min(std::max<size_t>(ix * pooling_width() + px, padding_left()) - padding_left(), output_width() - 1); |
| 387 | output_ref[((i * output_height() + oy) * output_width() + ox) * channels() + c] = |
| 388 | input[((i * input_height() + iy) * input_width() + ix) * input_pixel_stride() + c]; |
| 389 | } |
| 390 | } |
| 391 | } |
| 392 | } |
| 393 | |
| 394 | // Create, setup, and run Unpooling operator once. |
Marat Dukhan | 04f03be | 2019-11-19 12:36:47 -0800 | [diff] [blame] | 395 | ASSERT_EQ(xnn_status_success, xnn_initialize(nullptr /* allocator */)); |
XNNPACK Team | b455b12 | 2019-09-27 18:10:33 -0700 | [diff] [blame] | 396 | xnn_operator_t unpooling_op = nullptr; |
| 397 | |
| 398 | ASSERT_EQ(xnn_status_success, |
| 399 | xnn_create_unpooling2d_nhwc_x32( |
| 400 | padding_top(), padding_right(), padding_bottom(), padding_left(), |
| 401 | pooling_height(), pooling_width(), |
| 402 | channels(), input_pixel_stride(), output_pixel_stride(), |
| 403 | 0, &unpooling_op)); |
| 404 | ASSERT_NE(nullptr, unpooling_op); |
| 405 | |
| 406 | // Smart pointer to automatically delete unpooling_op. |
| 407 | std::unique_ptr<xnn_operator, decltype(&xnn_delete_operator)> auto_unpooling_op(unpooling_op, xnn_delete_operator); |
| 408 | |
| 409 | ASSERT_EQ(xnn_status_success, |
| 410 | xnn_setup_unpooling2d_nhwc_x32( |
| 411 | unpooling_op, |
| 412 | batch_size(), input_height(), input_width(), |
| 413 | input.data(), index.data(), output.data(), |
| 414 | nullptr /* thread pool */)); |
| 415 | |
| 416 | ASSERT_EQ(xnn_status_success, |
| 417 | xnn_run_operator(unpooling_op, nullptr /* thread pool */)); |
| 418 | |
| 419 | // Verify results of the first run. |
| 420 | for (size_t i = 0; i < batch_size(); i++) { |
| 421 | for (size_t c = 0; c < channels(); c++) { |
| 422 | for (size_t y = 0; y < output_height(); y++) { |
| 423 | for (size_t x = 0; x < output_width(); x++) { |
| 424 | EXPECT_EQ(output_ref[((i * output_height() + y) * output_width() + x) * channels() + c], |
| 425 | output[((i * output_height() + y) * output_width() + x) * output_pixel_stride() + c]) << |
| 426 | "in batch index " << i << ", pixel (" << y << ", " << x << "), channel " << c; |
| 427 | } |
| 428 | } |
| 429 | } |
| 430 | } |
| 431 | |
| 432 | // Re-generate data for the second run. |
| 433 | std::generate(input.begin(), input.end(), std::ref(u32rng)); |
| 434 | std::generate(index.begin(), index.end(), std::ref(idx_rng)); |
| 435 | std::generate(output.begin(), output.end(), std::ref(u32rng)); |
| 436 | |
| 437 | // Compute reference results for the second run, including clamping. |
| 438 | std::fill(next_output_ref.begin(), next_output_ref.end(), 0); |
| 439 | for (size_t i = 0; i < next_batch_size(); i++) { |
| 440 | for (size_t iy = 0; iy < next_input_height(); iy++) { |
| 441 | for (size_t ix = 0; ix < next_input_width(); ix++) { |
| 442 | for (size_t c = 0; c < channels(); c++) { |
| 443 | const uint32_t pooling_index = index[((i * next_input_height() + iy) * next_input_width() + ix) * channels() + c]; |
| 444 | const uint32_t py = pooling_index % pooling_height(); |
| 445 | const uint32_t px = pooling_index / pooling_height(); |
| 446 | const size_t oy = std::min(std::max<size_t>(iy * pooling_height() + py, padding_top()) - padding_top(), next_output_height() - 1); |
| 447 | const size_t ox = std::min(std::max<size_t>(ix * pooling_width() + px, padding_left()) - padding_left(), next_output_width() - 1); |
| 448 | next_output_ref[((i * next_output_height() + oy) * next_output_width() + ox) * channels() + c] = |
| 449 | input[((i * next_input_height() + iy) * next_input_width() + ix) * input_pixel_stride() + c]; |
| 450 | } |
| 451 | } |
| 452 | } |
| 453 | } |
| 454 | |
| 455 | // Setup and run Max Pooling operator the second time, and destroy the operator. |
| 456 | ASSERT_EQ(xnn_status_success, |
| 457 | xnn_setup_unpooling2d_nhwc_x32( |
| 458 | unpooling_op, |
| 459 | next_batch_size(), next_input_height(), next_input_width(), |
| 460 | input.data(), index.data(), output.data(), |
| 461 | nullptr /* thread pool */)); |
| 462 | |
| 463 | ASSERT_EQ(xnn_status_success, |
| 464 | xnn_run_operator(unpooling_op, nullptr /* thread pool */)); |
| 465 | |
| 466 | // Verify results of the second run. |
| 467 | for (size_t i = 0; i < next_batch_size(); i++) { |
| 468 | for (size_t c = 0; c < channels(); c++) { |
| 469 | for (size_t y = 0; y < next_output_height(); y++) { |
| 470 | for (size_t x = 0; x < next_output_width(); x++) { |
| 471 | EXPECT_EQ(next_output_ref[((i * next_output_height() + y) * next_output_width() + x) * channels() + c], |
| 472 | output[((i * next_output_height() + y) * next_output_width() + x) * output_pixel_stride() + c]) << |
| 473 | "in batch index " << i << ", pixel (" << y << ", " << x << "), channel " << c; |
| 474 | } |
| 475 | } |
| 476 | } |
| 477 | } |
| 478 | } |
| 479 | } |
| 480 | |
| 481 | private: |
| 482 | uint32_t padding_top_{0}; |
| 483 | uint32_t padding_right_{0}; |
| 484 | uint32_t padding_bottom_{0}; |
| 485 | uint32_t padding_left_{0}; |
| 486 | size_t input_height_{1}; |
| 487 | size_t input_width_{1}; |
| 488 | size_t channels_{1}; |
| 489 | size_t batch_size_{1}; |
| 490 | size_t input_pixel_stride_{0}; |
| 491 | size_t output_pixel_stride_{0}; |
| 492 | uint32_t pooling_height_{1}; |
| 493 | uint32_t pooling_width_{1}; |
| 494 | size_t next_input_height_{0}; |
| 495 | size_t next_input_width_{0}; |
| 496 | size_t next_batch_size_{0}; |
| 497 | size_t iterations_{1}; |
| 498 | }; |