John Kesapides | 8d94269 | 2019-02-26 14:52:12 +0000 | [diff] [blame] | 1 | /* |
| 2 | * Copyright (c) 2019 ARM Limited. |
| 3 | * |
| 4 | * SPDX-License-Identifier: MIT |
| 5 | * |
| 6 | * Permission is hereby granted, free of charge, to any person obtaining a copy |
| 7 | * of this software and associated documentation files (the "Software"), to |
| 8 | * deal in the Software without restriction, including without limitation the |
| 9 | * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or |
| 10 | * sell copies of the Software, and to permit persons to whom the Software is |
| 11 | * furnished to do so, subject to the following conditions: |
| 12 | * |
| 13 | * The above copyright notice and this permission notice shall be included in all |
| 14 | * copies or substantial portions of the Software. |
| 15 | * |
| 16 | * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR |
| 17 | * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, |
| 18 | * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE |
| 19 | * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER |
| 20 | * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, |
| 21 | * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE |
| 22 | * SOFTWARE. |
| 23 | */ |
| 24 | |
| 25 | #ifndef __GRAPH_VALIDATE_UTILS_H__ |
| 26 | #define __GRAPH_VALIDATE_UTILS_H__ |
| 27 | |
| 28 | #include "arm_compute/graph.h" |
| 29 | |
| 30 | #include "ValidateExample.h" |
| 31 | #include "utils/command_line/CommandLineParser.h" |
| 32 | |
| 33 | namespace arm_compute |
| 34 | { |
| 35 | namespace utils |
| 36 | { |
| 37 | /*Available Padding modes */ |
| 38 | enum class ConvolutionPaddingMode |
| 39 | { |
| 40 | Valid, |
| 41 | Same, |
| 42 | Manual |
| 43 | }; |
| 44 | |
| 45 | /** Stream Input operator for the ConvolutionPaddingMode type |
| 46 | * |
| 47 | * @param[in] stream Input stream. |
| 48 | * @param[out] Mode Convolution parameters to output |
| 49 | * |
| 50 | * @return input stream. |
| 51 | */ |
| 52 | inline ::std::istream &operator>>(::std::istream &stream, ConvolutionPaddingMode &Mode) |
| 53 | { |
| 54 | static const std::map<std::string, ConvolutionPaddingMode> modes = |
| 55 | { |
| 56 | { "valid", ConvolutionPaddingMode::Valid }, |
| 57 | { "same", ConvolutionPaddingMode::Same }, |
| 58 | { "manual", ConvolutionPaddingMode::Manual } |
| 59 | }; |
| 60 | std::string value; |
| 61 | stream >> value; |
| 62 | #ifndef ARM_COMPUTE_EXCEPTIONS_DISABLED |
| 63 | try |
| 64 | { |
| 65 | #endif /* ARM_COMPUTE_EXCEPTIONS_DISABLED */ |
| 66 | Mode = modes.at(arm_compute::utility::tolower(value)); |
| 67 | #ifndef ARM_COMPUTE_EXCEPTIONS_DISABLED |
| 68 | } |
| 69 | catch(const std::out_of_range &) |
| 70 | { |
| 71 | throw std::invalid_argument(value); |
| 72 | } |
| 73 | #endif /* ARM_COMPUTE_EXCEPTIONS_DISABLED */ |
| 74 | |
| 75 | return stream; |
| 76 | } |
| 77 | |
| 78 | /** Formatted output of the ConvolutionPaddingMode type |
| 79 | * |
| 80 | * @param[out] os Output stream. |
| 81 | * @param[in] Mode ConvolutionPaddingMode to output |
| 82 | * |
| 83 | * @return Modified output stream. |
| 84 | */ |
| 85 | inline ::std::ostream &operator<<(::std::ostream &os, ConvolutionPaddingMode Mode) |
| 86 | { |
| 87 | switch(Mode) |
| 88 | { |
| 89 | case ConvolutionPaddingMode::Valid: |
| 90 | os << "Valid"; |
| 91 | break; |
| 92 | case ConvolutionPaddingMode::Same: |
| 93 | os << "Same"; |
| 94 | break; |
| 95 | case ConvolutionPaddingMode::Manual: |
| 96 | os << "Manual"; |
| 97 | break; |
| 98 | default: |
| 99 | throw std::invalid_argument("Unsupported padding mode format"); |
| 100 | } |
| 101 | |
| 102 | return os; |
| 103 | } |
| 104 | |
| 105 | /** Structure holding all the input tensor graph parameters */ |
| 106 | struct TensorParams |
| 107 | { |
| 108 | int width{ 1 }; |
| 109 | int height{ 1 }; |
| 110 | int fm{ 1 }; |
| 111 | int batch{ 1 }; |
| 112 | QuantizationInfo quant_info{ 1.0f, 0 }; |
| 113 | std::string npy{}; |
| 114 | uint64_t range_low{ 0 }; |
| 115 | uint64_t range_high{ 16 }; |
| 116 | }; |
| 117 | |
| 118 | /** Structure holding all the verification graph parameters */ |
| 119 | struct VerificationParams |
| 120 | { |
| 121 | float absolute_tolerance{ -1.f }; |
| 122 | float relative_tolerance{ -1.f }; |
| 123 | float tolerance_number{ -1.f }; |
| 124 | }; |
| 125 | |
| 126 | /** Structure holding all the common graph parameters */ |
| 127 | struct FrameworkParams |
| 128 | { |
| 129 | bool help{ false }; |
| 130 | int threads{ 0 }; |
| 131 | arm_compute::graph::Target target{ arm_compute::graph::Target::NEON }; |
| 132 | }; |
| 133 | |
| 134 | /** Structure holding all the graph Example parameters */ |
| 135 | struct CommonParams |
| 136 | { |
| 137 | FrameworkParams common_params{}; |
| 138 | TensorParams input{}; |
| 139 | TensorParams weights{}; |
| 140 | TensorParams bias{}; |
| 141 | TensorParams output{}; |
| 142 | VerificationParams verification{}; |
| 143 | arm_compute::DataType data_type{ DataType::F32 }; |
| 144 | }; |
| 145 | |
| 146 | /** Structure holding all the Convolution layer graph parameters */ |
| 147 | struct ConvolutionParams |
| 148 | { |
| 149 | int depth_multiplier{ 1 }; |
| 150 | /** Padding graph parameters */ |
| 151 | int padding_top{ 0 }; |
| 152 | int padding_bottom{ 0 }; |
| 153 | int padding_left{ 0 }; |
| 154 | int padding_right{ 0 }; |
| 155 | int padding_stride_x{ 0 }; |
| 156 | int padding_stride_y{ 0 }; |
| 157 | ConvolutionPaddingMode padding_mode{ ConvolutionPaddingMode::Valid }; |
| 158 | struct |
| 159 | { |
| 160 | struct |
| 161 | { |
| 162 | int X{ 0 }; |
| 163 | int Y{ 0 }; |
| 164 | } stride{}; |
| 165 | ConvolutionPaddingMode mode{ ConvolutionPaddingMode::Valid }; |
| 166 | } padding{}; |
| 167 | }; |
| 168 | |
| 169 | /** Structure holding all the fully_connected layer graph parameters */ |
| 170 | struct FullyConnectedParams |
| 171 | { |
| 172 | FullyConnectedLayerInfo info{}; |
| 173 | int num_outputs{ 1 }; |
| 174 | }; |
| 175 | |
| 176 | /** Structure holding all the graph Example parameters */ |
| 177 | struct ExampleParams : public CommonParams |
| 178 | { |
| 179 | FullyConnectedParams fully_connected{}; |
| 180 | ConvolutionParams convolution{}; |
| 181 | arm_compute::graph::DepthwiseConvolutionMethod depth_convolution_method{ arm_compute::graph::DepthwiseConvolutionMethod::Default }; |
| 182 | arm_compute::graph::ConvolutionMethod convolution_method{ arm_compute::graph::ConvolutionMethod::Default }; |
| 183 | arm_compute::DataLayout data_layout{ DataLayout::NCHW }; |
| 184 | }; |
| 185 | |
| 186 | /** Calculate stride information. |
| 187 | * |
| 188 | * Depending on the selected padding mode create the desired PadStrideInfo |
| 189 | * |
| 190 | * @param[in] params Convolution parameters supplied by the user. |
| 191 | * |
| 192 | * @return PadStrideInfo with the correct padding mode. |
| 193 | */ |
| 194 | inline PadStrideInfo calculate_convolution_padding(ExampleParams params) |
| 195 | { |
| 196 | switch(params.convolution.padding_mode) |
| 197 | { |
| 198 | case ConvolutionPaddingMode::Manual: |
| 199 | { |
| 200 | return PadStrideInfo(params.convolution.padding_stride_x, params.convolution.padding_stride_y, params.convolution.padding_left, params.convolution.padding_right, params.convolution.padding_top, |
| 201 | params.convolution.padding_bottom, DimensionRoundingType::FLOOR); |
| 202 | } |
| 203 | case ConvolutionPaddingMode::Valid: |
| 204 | { |
| 205 | return PadStrideInfo(); |
| 206 | } |
| 207 | case ConvolutionPaddingMode::Same: |
| 208 | { |
| 209 | return arm_compute::calculate_same_pad(TensorShape(params.input.width, params.input.height), TensorShape(params.weights.width, params.weights.height), |
| 210 | PadStrideInfo(params.convolution.padding_stride_x, |
| 211 | params.convolution.padding_stride_y)); |
| 212 | } |
| 213 | default: |
| 214 | ARM_COMPUTE_ERROR("NOT SUPPORTED!"); |
| 215 | } |
| 216 | } |
| 217 | /** CommonGraphValidateOptions command line options used to configure the graph examples |
| 218 | * |
| 219 | * (Similar to common options) |
| 220 | * The options in this object get populated when "parse()" is called on the parser used to construct it. |
| 221 | * The expected workflow is: |
| 222 | * |
| 223 | * CommandLineParser parser; |
| 224 | * CommonOptions options( parser ); |
| 225 | * parser.parse(argc, argv); |
| 226 | */ |
| 227 | class CommonGraphValidateOptions |
| 228 | { |
| 229 | public: |
| 230 | explicit CommonGraphValidateOptions(CommandLineParser &parser) noexcept |
| 231 | : help(parser.add_option<ToggleOption>("help")), |
| 232 | threads(parser.add_option<SimpleOption<int>>("threads")), |
| 233 | target(), |
| 234 | data_type(), |
| 235 | absolute_tolerance(parser.add_option<SimpleOption<float>>("abs_tolerance", -1.0f)), |
| 236 | relative_tolerance(parser.add_option<SimpleOption<float>>("rel_tolerance", -1.0f)), |
| 237 | tolerance_number(parser.add_option<SimpleOption<float>>("tolerance_num", -1.0f)) |
| 238 | { |
| 239 | const std::set<arm_compute::graph::Target> supported_targets |
| 240 | { |
| 241 | arm_compute::graph::Target::NEON, |
| 242 | arm_compute::graph::Target::CL, |
| 243 | arm_compute::graph::Target::GC, |
| 244 | }; |
| 245 | |
| 246 | const std::set<arm_compute::DataType> supported_data_types |
| 247 | { |
| 248 | DataType::F16, |
| 249 | DataType::F32, |
| 250 | DataType::QASYMM8, |
| 251 | }; |
| 252 | |
| 253 | target = parser.add_option<EnumOption<arm_compute::graph::Target>>("target", supported_targets, arm_compute::graph::Target::NEON); |
| 254 | data_type = parser.add_option<EnumOption<DataType>>("type", supported_data_types, DataType::F32); |
| 255 | |
| 256 | target->set_help("Target to execute on"); |
| 257 | data_type->set_help("Data type to use"); |
| 258 | help->set_help("Show this help message"); |
| 259 | absolute_tolerance->set_help("Absolute tolerance used for verification"); |
| 260 | relative_tolerance->set_help("Absolute tolerance used for verification"); |
| 261 | tolerance_number->set_help("Absolute tolerance used for verification"); |
| 262 | ; |
| 263 | } |
| 264 | |
| 265 | /** Prevent instances of this class from being copied (As this class contains pointers) */ |
| 266 | CommonGraphValidateOptions(const CommonGraphValidateOptions &) = delete; |
| 267 | /** Prevent instances of this class from being copied (As this class contains pointers) */ |
| 268 | CommonGraphValidateOptions &operator=(const CommonGraphValidateOptions &) = delete; |
| 269 | /** Allow instances of this class to be moved */ |
| 270 | CommonGraphValidateOptions(CommonGraphValidateOptions &&) noexcept(true) = default; |
| 271 | /** Allow instances of this class to be moved */ |
| 272 | CommonGraphValidateOptions &operator=(CommonGraphValidateOptions &&) noexcept(true) = default; |
| 273 | /** Default destructor */ |
| 274 | virtual ~CommonGraphValidateOptions() = default; |
| 275 | |
| 276 | void consume_common_parameters(CommonParams &common_params) |
| 277 | { |
| 278 | common_params.common_params.help = help->is_set() ? help->value() : false; |
| 279 | common_params.common_params.threads = threads->value(); |
| 280 | common_params.common_params.target = target->value(); |
| 281 | |
| 282 | common_params.verification.absolute_tolerance = absolute_tolerance->value(); |
| 283 | common_params.verification.relative_tolerance = relative_tolerance->value(); |
| 284 | common_params.verification.tolerance_number = tolerance_number->value(); |
| 285 | } |
| 286 | |
| 287 | /** Formatted output of the ExampleParams type |
| 288 | * |
| 289 | * @param[out] os Output stream. |
| 290 | * @param[in] common_params Example parameters to output |
| 291 | * |
| 292 | * @return None. |
| 293 | */ |
| 294 | virtual void print_parameters(::std::ostream &os, const ExampleParams &common_params) |
| 295 | { |
| 296 | os << "Threads : " << common_params.common_params.threads << std::endl; |
| 297 | os << "Target : " << common_params.common_params.target << std::endl; |
| 298 | os << "Data type : " << common_params.data_type << std::endl; |
| 299 | } |
| 300 | |
| 301 | ToggleOption *help; /**< show help message */ |
| 302 | SimpleOption<int> *threads; /**< Number of threads option */ |
| 303 | EnumOption<arm_compute::graph::Target> *target; /**< Graph execution target */ |
| 304 | EnumOption<arm_compute::DataType> *data_type; /**< Graph data type */ |
| 305 | SimpleOption<float> *absolute_tolerance; /**< Absolute tolerance used in verification */ |
| 306 | SimpleOption<float> *relative_tolerance; /**< Relative tolerance used in verification */ |
| 307 | SimpleOption<float> *tolerance_number; /**< Tolerance number used in verification */ |
| 308 | }; |
| 309 | |
| 310 | /** Consumes the consume_common_graph_parameters graph options and creates a structure containing any information |
| 311 | * |
| 312 | * @param[in] options Options to consume |
| 313 | * @param[out] common_params params structure to consume. |
| 314 | * |
| 315 | * @return consume_common_graph_parameters structure containing the common graph parameters |
| 316 | */ |
| 317 | void consume_common_graph_parameters(CommonGraphValidateOptions &options, CommonParams &common_params) |
| 318 | { |
| 319 | common_params.common_params.help = options.help->is_set() ? options.help->value() : false; |
| 320 | common_params.common_params.threads = options.threads->value(); |
| 321 | common_params.common_params.target = options.target->value(); |
| 322 | |
| 323 | common_params.verification.absolute_tolerance = options.absolute_tolerance->value(); |
| 324 | common_params.verification.relative_tolerance = options.relative_tolerance->value(); |
| 325 | common_params.verification.tolerance_number = options.tolerance_number->value(); |
| 326 | } |
| 327 | |
| 328 | /** Generates appropriate accessor according to the specified graph parameters |
| 329 | * |
| 330 | * @param[in] tensor Tensor parameters |
| 331 | * @param[in] lower Lower random values bound |
| 332 | * @param[in] upper Upper random values bound |
| 333 | * @param[in] seed Random generator seed |
| 334 | * |
| 335 | * @return An appropriate tensor accessor |
| 336 | */ |
| 337 | inline std::unique_ptr<graph::ITensorAccessor> get_accessor(const TensorParams &tensor, PixelValue lower, PixelValue upper, const std::random_device::result_type seed = 0) |
| 338 | { |
| 339 | if(!tensor.npy.empty()) |
| 340 | { |
| 341 | return arm_compute::support::cpp14::make_unique<arm_compute::graph_utils::NumPyBinLoader>(tensor.npy); |
| 342 | } |
| 343 | else |
| 344 | { |
| 345 | return arm_compute::support::cpp14::make_unique<arm_compute::graph_utils::RandomAccessor>(lower, upper, seed); |
| 346 | } |
| 347 | } |
| 348 | |
| 349 | /** Graph example validation accessor class */ |
| 350 | template <typename D> |
| 351 | class VerifyAccessor : public graph::ITensorAccessor |
| 352 | { |
| 353 | public: |
| 354 | using TBias = typename std::conditional<std::is_same<typename std::decay<D>::type, uint8_t>::value, int32_t, D>::type; |
| 355 | /** Constructor |
| 356 | * |
| 357 | * @param[in] params Convolution parameters |
| 358 | */ |
| 359 | explicit VerifyAccessor(ExampleParams ¶ms) |
| 360 | : _params(std::move(params)) |
| 361 | { |
| 362 | } |
| 363 | // Inherited methods overriden: |
| 364 | bool access_tensor(ITensor &tensor) override |
| 365 | { |
| 366 | if(_params.output.npy.empty()) |
| 367 | { |
| 368 | arm_compute::test::SimpleTensor<D> src; |
| 369 | arm_compute::test::SimpleTensor<D> weights; |
| 370 | arm_compute::test::SimpleTensor<TBias> bias; |
| 371 | |
| 372 | //Create Input tensors |
| 373 | create_tensors(src, weights, bias, tensor); |
| 374 | |
| 375 | //Fill the tensors with random values |
| 376 | fill_tensor(src, 0, static_cast<D>(_params.input.range_low), static_cast<D>(_params.input.range_high)); |
| 377 | fill_tensor(weights, 1, static_cast<D>(_params.weights.range_low), static_cast<D>(_params.weights.range_high)); |
| 378 | fill_tensor(bias, 2, static_cast<TBias>(_params.input.range_low), static_cast<TBias>(_params.input.range_high)); |
| 379 | |
| 380 | arm_compute::test::SimpleTensor<D> output = reference(src, weights, bias, output_shape(tensor)); |
| 381 | |
| 382 | validate(tensor, output); |
| 383 | } |
| 384 | else |
| 385 | { |
| 386 | //The user provided a reference file use an npy accessor to validate |
| 387 | arm_compute::graph_utils::NumPyAccessor(_params.output.npy, tensor.info()->tensor_shape(), tensor.info()->data_type()).access_tensor(tensor); |
| 388 | } |
| 389 | return false; |
| 390 | } |
| 391 | |
| 392 | /** Create reference tensors. |
| 393 | * |
| 394 | * Validate the given tensor against the reference result. |
| 395 | * |
| 396 | * @param[out] src The tensor with the source data. |
| 397 | * @param[out] weights The tensor with the weigths data. |
| 398 | * @param[out] bias The tensor with the bias data. |
| 399 | * @param[in] tensor Tensor result of the actual operation passed into the Accessor. |
| 400 | * |
| 401 | * @return None. |
| 402 | */ |
| 403 | virtual void create_tensors(arm_compute::test::SimpleTensor<D> &src, |
| 404 | arm_compute::test::SimpleTensor<D> &weights, |
| 405 | arm_compute::test::SimpleTensor<TBias> &bias, |
| 406 | ITensor &tensor) |
| 407 | { |
| 408 | //Create Input tensors |
| 409 | src = arm_compute::test::SimpleTensor<D> { TensorShape(_params.input.width, _params.input.height, _params.input.fm, _params.input.batch), _params.data_type, 1, _params.input.quant_info }; |
| 410 | weights = arm_compute::test::SimpleTensor<D> { TensorShape(_params.weights.width, _params.weights.height, _params.weights.fm), _params.data_type, 1, _params.weights.quant_info }; |
| 411 | bias = arm_compute::test::SimpleTensor<TBias> { TensorShape(_params.input.height), _params.data_type, 1, _params.input.quant_info }; |
| 412 | } |
| 413 | |
| 414 | /** Calculate reference output tensor shape. |
| 415 | * |
| 416 | * @param[in] tensor Tensor result of the actual operation passed into the Accessor. |
| 417 | * |
| 418 | * @return output tensor shape. |
| 419 | */ |
| 420 | virtual TensorShape output_shape(ITensor &tensor) |
| 421 | { |
| 422 | return arm_compute::graph_utils::permute_shape(tensor.info()->tensor_shape(), _params.data_layout, DataLayout::NCHW); |
| 423 | } |
| 424 | |
| 425 | /** Calculate reference tensor. |
| 426 | * |
| 427 | * Validate the given tensor against the reference result. |
| 428 | * |
| 429 | * @param[in] src The tensor with the source data. |
| 430 | * @param[in] weights The tensor with the weigths data. |
| 431 | * @param[in] bias The tensor with the bias data. |
| 432 | * @param[in] output_shape Shape of the output tensor. |
| 433 | * |
| 434 | * @return Tensor with the reference output. |
| 435 | */ |
| 436 | virtual arm_compute::test::SimpleTensor<D> reference(arm_compute::test::SimpleTensor<D> &src, |
| 437 | arm_compute::test::SimpleTensor<D> &weights, |
| 438 | arm_compute::test::SimpleTensor<TBias> &bias, |
| 439 | const arm_compute::TensorShape &output_shape) = 0; |
| 440 | |
| 441 | /** Fill QASYMM tensor with Random values. |
| 442 | * |
| 443 | * Validate the given tensor against the reference result. |
| 444 | * |
| 445 | * @param[out] tensor The tensor we want to file |
| 446 | * @param[in] seed seed for the randomization function |
| 447 | * @param[in] low lower bound for random values |
| 448 | * @param[in] high upper bound for random values |
| 449 | * |
| 450 | * @return None. |
| 451 | */ |
| 452 | void fill_tensor(arm_compute::test::SimpleTensor<uint8_t> &tensor, std::random_device::result_type seed, uint8_t low, uint8_t high) |
| 453 | { |
| 454 | ARM_COMPUTE_ERROR_ON(tensor.data_type() != arm_compute::DataType::QASYMM8); |
| 455 | |
| 456 | std::mt19937 gen(seed); |
| 457 | |
| 458 | uint8_t qasymm8_low = tensor.quantization_info().quantize(low, RoundingPolicy::TO_NEAREST_UP); |
| 459 | uint8_t qasymm8_high = tensor.quantization_info().quantize(high, RoundingPolicy::TO_NEAREST_UP); |
| 460 | |
| 461 | std::uniform_int_distribution<uint8_t> distribution(qasymm8_low, qasymm8_high); |
| 462 | |
| 463 | for(int i = 0; i < tensor.num_elements(); ++i) |
| 464 | { |
| 465 | tensor[i] = tensor.quantization_info().quantize(distribution(gen), RoundingPolicy::TO_NEAREST_UP); |
| 466 | } |
| 467 | } |
| 468 | /** Fill S32 tensor with Random values. |
| 469 | * |
| 470 | * Validate the given tensor against the reference result. |
| 471 | * |
| 472 | * @param[out] tensor The tensor we want to file |
| 473 | * @param[in] seed seed for the randomization function |
| 474 | * @param[in] low lower bound for random values |
| 475 | * @param[in] high upper bound for random values |
| 476 | * |
| 477 | * @return None. |
| 478 | */ |
| 479 | void fill_tensor(arm_compute::test::SimpleTensor<int32_t> &tensor, std::random_device::result_type seed, int32_t low, int32_t high) |
| 480 | { |
| 481 | std::mt19937 gen(seed); |
| 482 | std::uniform_int_distribution<int32_t> distribution(static_cast<int32_t>(low), static_cast<uint32_t>(high)); |
| 483 | |
| 484 | for(int i = 0; i < tensor.num_elements(); ++i) |
| 485 | { |
| 486 | tensor[i] = distribution(gen); |
| 487 | } |
| 488 | } |
| 489 | /** Fill F32 tensor with Random values. |
| 490 | * |
| 491 | * Validate the given tensor against the reference result. |
| 492 | * |
| 493 | * @param[out] tensor The tensor we want to file |
| 494 | * @param[in] seed seed for the randomization function |
| 495 | * @param[in] low lower bound for random values |
| 496 | * @param[in] high upper bound for random values |
| 497 | * |
| 498 | * @return None. |
| 499 | */ |
| 500 | void fill_tensor(arm_compute::test::SimpleTensor<float> &tensor, std::random_device::result_type seed, float low, float high) |
| 501 | { |
| 502 | ARM_COMPUTE_ERROR_ON(tensor.data_type() != arm_compute::DataType::F32); |
| 503 | std::mt19937 gen(seed); |
| 504 | std::uniform_real_distribution<float> distribution(low, high); |
| 505 | |
| 506 | for(int i = 0; i < tensor.num_elements(); ++i) |
| 507 | { |
| 508 | tensor[i] = distribution(gen); |
| 509 | } |
| 510 | } |
| 511 | /** Fill F16 tensor with Random values. |
| 512 | * |
| 513 | * Validate the given tensor against the reference result. |
| 514 | * |
| 515 | * @param[out] tensor The tensor we want to file |
| 516 | * @param[in] seed seed for the randomization function |
| 517 | * @param[in] low lower bound for random values |
| 518 | * @param[in] high upper bound for random values |
| 519 | * |
| 520 | * @return None. |
| 521 | */ |
| 522 | void fill_tensor(arm_compute::test::SimpleTensor<half> &tensor, std::random_device::result_type seed, half low, half high) |
| 523 | { |
| 524 | ARM_COMPUTE_ERROR_ON(tensor.data_type() != arm_compute::DataType::F16); |
| 525 | std::mt19937 gen(seed); |
| 526 | std::uniform_real_distribution<float> distribution(static_cast<half>(low), static_cast<half>(high)); |
| 527 | |
| 528 | for(int i = 0; i < tensor.num_elements(); ++i) |
| 529 | { |
| 530 | tensor[i] = static_cast<half>(distribution(gen)); |
| 531 | } |
| 532 | } |
| 533 | |
| 534 | /** Select relative tolerance. |
| 535 | * |
| 536 | * Select relative tolerance if not supplied by user. |
| 537 | * |
| 538 | * @return Appropriate relative tolerance. |
| 539 | */ |
| 540 | virtual float relative_tolerance() = 0; |
| 541 | |
| 542 | /** Select absolute tolerance. |
| 543 | * |
| 544 | * Select absolute tolerance if not supplied by user. |
| 545 | * |
| 546 | * @return Appropriate absolute tolerance. |
| 547 | */ |
| 548 | virtual float absolute_tolerance() = 0; |
| 549 | |
| 550 | /** Select tolerance number. |
| 551 | * |
| 552 | * Select tolerance number if not supplied by user. |
| 553 | * |
| 554 | * @return Appropriate tolerance number. |
| 555 | */ |
| 556 | virtual float tolerance_number() = 0; |
| 557 | |
| 558 | /** Validate the output versus the reference. |
| 559 | * |
| 560 | * @param[in] tensor Tensor result of the actual operation passed into the Accessor. |
| 561 | * @param[in] output Tensor result of the reference implementation. |
| 562 | * |
| 563 | * @return None. |
| 564 | */ |
| 565 | void validate(ITensor &tensor, arm_compute::test::SimpleTensor<D> output) |
| 566 | { |
| 567 | float user_relative_tolerance = _params.verification.relative_tolerance; |
| 568 | float user_absolute_tolerance = _params.verification.absolute_tolerance; |
| 569 | float user_tolerance_num = _params.verification.tolerance_number; |
| 570 | /* If no user input was provided override with defaults. */ |
| 571 | if(user_relative_tolerance == -1) |
| 572 | { |
| 573 | user_relative_tolerance = relative_tolerance(); |
| 574 | } |
| 575 | |
| 576 | if(user_absolute_tolerance == -1) |
| 577 | { |
| 578 | user_absolute_tolerance = absolute_tolerance(); |
| 579 | } |
| 580 | |
| 581 | if(user_tolerance_num == -1) |
| 582 | { |
| 583 | user_tolerance_num = tolerance_number(); |
| 584 | } |
| 585 | |
| 586 | const arm_compute::test::validation::RelativeTolerance<float> rel_tolerance(user_relative_tolerance); /**< Relative tolerance */ |
| 587 | const arm_compute::test::validation::AbsoluteTolerance<float> abs_tolerance(user_absolute_tolerance); /**< Absolute tolerance */ |
| 588 | const float tolerance_num(user_tolerance_num); /**< Tolerance number */ |
| 589 | |
| 590 | arm_compute::test::validation::validate(arm_compute::test::Accessor(tensor), output, rel_tolerance, tolerance_num, abs_tolerance); |
| 591 | } |
| 592 | |
| 593 | ExampleParams _params; |
| 594 | }; |
| 595 | |
| 596 | /** Generates appropriate convolution verify accessor |
| 597 | * |
| 598 | * @param[in] params User supplied parameters for convolution. |
| 599 | * |
| 600 | * @return A convolution verify accessor for the requested datatype. |
| 601 | */ |
| 602 | template <template <typename D> class VerifyAccessorT> |
| 603 | inline std::unique_ptr<graph::ITensorAccessor> get_verify_accessor(ExampleParams params) |
| 604 | { |
| 605 | switch(params.data_type) |
| 606 | { |
| 607 | case DataType::QASYMM8: |
| 608 | { |
| 609 | return arm_compute::support::cpp14::make_unique<VerifyAccessorT<uint8_t>>( |
| 610 | params); |
| 611 | } |
| 612 | case DataType::F16: |
| 613 | { |
| 614 | return arm_compute::support::cpp14::make_unique<VerifyAccessorT<half>>( |
| 615 | params); |
| 616 | } |
| 617 | case DataType::F32: |
| 618 | { |
| 619 | return arm_compute::support::cpp14::make_unique<VerifyAccessorT<float>>( |
| 620 | params); |
| 621 | } |
| 622 | default: |
| 623 | ARM_COMPUTE_ERROR("NOT SUPPORTED!"); |
| 624 | } |
| 625 | } |
| 626 | |
| 627 | template <typename LayerT, typename OptionsT, template <typename D> class VerifyAccessorT> |
| 628 | class GraphValidateExample : public ValidateExample |
| 629 | { |
| 630 | public: |
| 631 | GraphValidateExample(std::string name) |
| 632 | : graph(0, name) |
| 633 | { |
| 634 | } |
| 635 | |
| 636 | virtual LayerT GraphFunctionLayer(ExampleParams ¶ms) = 0; |
| 637 | |
| 638 | bool do_setup(int argc, char **argv) override |
| 639 | { |
| 640 | CommandLineParser parser; |
| 641 | |
| 642 | OptionsT Options(parser); |
| 643 | |
| 644 | parser.parse(argc, argv); |
| 645 | |
| 646 | ExampleParams params; |
| 647 | |
| 648 | Options.consume_common_parameters(params); |
| 649 | Options.consume_parameters(params); |
| 650 | |
| 651 | if(params.common_params.help) |
| 652 | { |
| 653 | parser.print_help(argv[0]); |
| 654 | return false; |
| 655 | } |
| 656 | |
| 657 | Options.print_parameters(std::cout, params); |
| 658 | // Create input descriptor |
| 659 | const TensorShape input_shape = arm_compute::graph_utils::permute_shape(TensorShape(params.input.width, params.input.height, params.input.fm, params.input.batch), |
| 660 | DataLayout::NCHW, params.data_layout); |
| 661 | arm_compute::graph::TensorDescriptor input_descriptor = arm_compute::graph::TensorDescriptor(input_shape, params.data_type, params.input.quant_info, params.data_layout); |
| 662 | |
| 663 | const PixelValue lower = PixelValue(params.input.range_low, params.data_type, params.input.quant_info); |
| 664 | const PixelValue upper = PixelValue(params.input.range_high, params.data_type, params.input.quant_info); |
| 665 | |
| 666 | graph << params.common_params.target |
| 667 | << params.convolution_method |
| 668 | << params.depth_convolution_method |
| 669 | << arm_compute::graph::frontend::InputLayer(input_descriptor, get_accessor(params.input, lower, upper, 0)) |
| 670 | << GraphFunctionLayer(params) |
| 671 | << arm_compute::graph::frontend::OutputLayer(get_verify_accessor<VerifyAccessorT>(params)); |
| 672 | |
| 673 | arm_compute::graph::GraphConfig config; |
| 674 | config.num_threads = params.common_params.threads; |
| 675 | |
| 676 | graph.finalize(params.common_params.target, config); |
| 677 | |
| 678 | return true; |
| 679 | } |
| 680 | |
| 681 | void do_run() override |
| 682 | { |
| 683 | graph.run(); |
| 684 | } |
| 685 | |
| 686 | void do_teardown() override |
| 687 | { |
| 688 | } |
| 689 | |
| 690 | arm_compute::graph::frontend::Stream graph; |
| 691 | }; |
| 692 | |
| 693 | } // graph_validate_utils |
| 694 | } // arm_compute |
| 695 | #endif //__GRAPH_VALIDATE_UTILS_H__ |