telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1 | // |
| 2 | // Copyright © 2017 Arm Ltd. All rights reserved. |
David Beck | ecb56cd | 2018-09-05 12:52:57 +0100 | [diff] [blame] | 3 | // SPDX-License-Identifier: MIT |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 4 | // |
| 5 | #include <boost/test/unit_test.hpp> |
| 6 | #include <backends/CpuTensorHandle.hpp> |
| 7 | #include <backends/Workload.hpp> |
David Beck | b4540be | 2018-09-24 13:18:27 +0100 | [diff] [blame] | 8 | #include <backends/reference/workloads/RefWorkloads.hpp> |
| 9 | #include <backends/reference/RefWorkloadFactory.hpp> |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 10 | |
| 11 | #include <armnn/Exceptions.hpp> |
| 12 | |
| 13 | #include "WorkloadTestUtils.hpp" |
| 14 | |
| 15 | using namespace armnn; |
| 16 | |
| 17 | BOOST_AUTO_TEST_SUITE(WorkloadInfoValidation) |
| 18 | |
| 19 | |
| 20 | |
| 21 | BOOST_AUTO_TEST_CASE(QueueDescriptor_Validate_WrongNumOfInputsOutputs) |
| 22 | { |
| 23 | InputQueueDescriptor invalidData; |
| 24 | WorkloadInfo invalidInfo; |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 25 | //Invalid argument exception is expected, because no inputs and no outputs were defined. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 26 | BOOST_CHECK_THROW(RefWorkloadFactory().CreateInput(invalidData, invalidInfo), armnn::InvalidArgumentException); |
| 27 | } |
| 28 | |
| 29 | BOOST_AUTO_TEST_CASE(RefPooling2dFloat32Workload_Validate_WrongDimTensor) |
| 30 | { |
| 31 | armnn::TensorInfo inputTensorInfo; |
| 32 | armnn::TensorInfo outputTensorInfo; |
| 33 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 34 | unsigned int inputShape[] = {2, 3, 4}; // <- Invalid - input tensor has to be 4D. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 35 | unsigned int outputShape[] = {2, 3, 4, 5}; |
| 36 | |
| 37 | outputTensorInfo = armnn::TensorInfo(4, outputShape, armnn::DataType::Float32); |
| 38 | inputTensorInfo = armnn::TensorInfo(3, inputShape, armnn::DataType::Float32); |
| 39 | |
| 40 | Pooling2dQueueDescriptor invalidData; |
| 41 | WorkloadInfo invalidInfo; |
| 42 | |
| 43 | AddOutputToWorkload(invalidData, invalidInfo, outputTensorInfo, nullptr); |
| 44 | AddInputToWorkload(invalidData, invalidInfo, inputTensorInfo, nullptr); |
| 45 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 46 | // Invalid argument exception is expected, input tensor has to be 4D. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 47 | BOOST_CHECK_THROW(RefPooling2dFloat32Workload(invalidData, invalidInfo), armnn::InvalidArgumentException); |
| 48 | } |
| 49 | |
| 50 | BOOST_AUTO_TEST_CASE(SoftmaxQueueDescriptor_Validate_WrongInputHeight) |
| 51 | { |
| 52 | unsigned int inputHeight = 1; |
| 53 | unsigned int inputWidth = 1; |
| 54 | unsigned int inputChannels = 4; |
| 55 | unsigned int inputNum = 2; |
| 56 | |
| 57 | unsigned int outputChannels = inputChannels; |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 58 | unsigned int outputHeight = inputHeight + 1; //Makes data invalid - Softmax expects height and width to be 1. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 59 | unsigned int outputWidth = inputWidth; |
| 60 | unsigned int outputNum = inputNum; |
| 61 | |
| 62 | armnn::TensorInfo inputTensorInfo; |
| 63 | armnn::TensorInfo outputTensorInfo; |
| 64 | |
| 65 | unsigned int inputShape[] = { inputNum, inputChannels, inputHeight, inputWidth }; |
| 66 | unsigned int outputShape[] = { outputNum, outputChannels, outputHeight, outputWidth }; |
| 67 | |
| 68 | inputTensorInfo = armnn::TensorInfo(4, inputShape, armnn::DataType::Float32); |
| 69 | outputTensorInfo = armnn::TensorInfo(4, outputShape, armnn::DataType::Float32); |
| 70 | |
| 71 | SoftmaxQueueDescriptor invalidData; |
| 72 | WorkloadInfo invalidInfo; |
| 73 | |
| 74 | AddInputToWorkload(invalidData, invalidInfo, inputTensorInfo, nullptr); |
| 75 | AddOutputToWorkload(invalidData, invalidInfo, outputTensorInfo, nullptr); |
| 76 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 77 | //Invalid argument exception is expected, because height != 1. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 78 | BOOST_CHECK_THROW(RefSoftmaxFloat32Workload(invalidData, invalidInfo), armnn::InvalidArgumentException); |
| 79 | } |
| 80 | |
| 81 | BOOST_AUTO_TEST_CASE(FullyConnectedQueueDescriptor_Validate_RequiredDataMissing) |
| 82 | { |
| 83 | unsigned int inputWidth = 1; |
| 84 | unsigned int inputHeight = 1; |
| 85 | unsigned int inputChannels = 5; |
| 86 | unsigned int inputNum = 2; |
| 87 | |
| 88 | unsigned int outputWidth = 1; |
| 89 | unsigned int outputHeight = 1; |
| 90 | unsigned int outputChannels = 3; |
| 91 | unsigned int outputNum = 2; |
| 92 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 93 | // Define the tensor descriptors. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 94 | armnn::TensorInfo inputTensorInfo; |
| 95 | armnn::TensorInfo outputTensorInfo; |
| 96 | armnn::TensorInfo weightsDesc; |
| 97 | armnn::TensorInfo biasesDesc; |
| 98 | |
| 99 | unsigned int inputShape[] = { inputNum, inputChannels, inputHeight, inputWidth }; |
| 100 | unsigned int outputShape[] = { outputNum, outputChannels, outputHeight, outputWidth }; |
| 101 | unsigned int weightsShape[] = { 1, 1, inputChannels, outputChannels }; |
| 102 | unsigned int biasShape[] = { 1, outputChannels, outputHeight, outputWidth }; |
| 103 | |
| 104 | inputTensorInfo = armnn::TensorInfo(4, inputShape, armnn::DataType::Float32); |
| 105 | outputTensorInfo = armnn::TensorInfo(4, outputShape, armnn::DataType::Float32); |
| 106 | weightsDesc = armnn::TensorInfo(4, weightsShape, armnn::DataType::Float32); |
| 107 | biasesDesc = armnn::TensorInfo(4, biasShape, armnn::DataType::Float32); |
| 108 | |
| 109 | FullyConnectedQueueDescriptor invalidData; |
| 110 | WorkloadInfo invalidInfo; |
| 111 | |
| 112 | ScopedCpuTensorHandle weightTensor(weightsDesc); |
| 113 | ScopedCpuTensorHandle biasTensor(biasesDesc); |
| 114 | |
| 115 | AddInputToWorkload(invalidData, invalidInfo, inputTensorInfo, nullptr); |
| 116 | AddOutputToWorkload(invalidData, invalidInfo, outputTensorInfo, nullptr); |
| 117 | invalidData.m_Weight = &weightTensor; |
| 118 | invalidData.m_Bias = &biasTensor; |
| 119 | invalidData.m_Parameters.m_BiasEnabled = true; |
| 120 | invalidData.m_Parameters.m_TransposeWeightMatrix = false; |
| 121 | |
| 122 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 123 | //Invalid argument exception is expected, because not all required fields have been provided. |
| 124 | //In particular inputsData[0], outputsData[0] and weightsData can not be null. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 125 | BOOST_CHECK_THROW(RefFullyConnectedFloat32Workload(invalidData, invalidInfo), armnn::InvalidArgumentException); |
| 126 | } |
| 127 | |
| 128 | |
| 129 | BOOST_AUTO_TEST_CASE(NormalizationQueueDescriptor_Validate_WrongInputHeight) |
| 130 | { |
| 131 | constexpr unsigned int inputNum = 5; |
| 132 | constexpr unsigned int inputHeight = 32; |
| 133 | constexpr unsigned int inputWidth = 24; |
| 134 | constexpr unsigned int inputChannels = 3; |
| 135 | |
| 136 | constexpr unsigned int outputNum = inputNum; |
| 137 | constexpr unsigned int outputChannels = inputChannels; |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 138 | constexpr unsigned int outputHeight = inputHeight + 1; //Makes data invalid - normalization requires. |
| 139 | //Input and output to have the same dimensions. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 140 | constexpr unsigned int outputWidth = inputWidth; |
| 141 | |
| 142 | |
| 143 | armnn::TensorInfo inputTensorInfo; |
| 144 | armnn::TensorInfo outputTensorInfo; |
| 145 | |
| 146 | unsigned int inputShape[] = {inputNum, inputChannels, inputHeight, inputWidth}; |
| 147 | unsigned int outputShape[] = {outputNum, outputChannels, outputHeight, outputWidth}; |
| 148 | |
| 149 | inputTensorInfo = armnn::TensorInfo(4, inputShape, armnn::DataType::Float32); |
| 150 | outputTensorInfo = armnn::TensorInfo(4, outputShape, armnn::DataType::Float32); |
| 151 | |
| 152 | |
| 153 | armnn::NormalizationAlgorithmMethod normMethod = armnn::NormalizationAlgorithmMethod::LocalBrightness; |
| 154 | armnn::NormalizationAlgorithmChannel normChannel = armnn::NormalizationAlgorithmChannel::Across; |
| 155 | float alpha = 1.f; |
| 156 | float beta = 1.f; |
| 157 | float kappa = 1.f; |
| 158 | uint32_t normSize = 5; |
| 159 | |
| 160 | NormalizationQueueDescriptor invalidData; |
| 161 | WorkloadInfo invalidInfo; |
| 162 | |
| 163 | AddInputToWorkload(invalidData, invalidInfo, inputTensorInfo, nullptr); |
| 164 | AddOutputToWorkload(invalidData, invalidInfo, outputTensorInfo, nullptr); |
| 165 | invalidData.m_Parameters.m_NormChannelType = normChannel; |
| 166 | invalidData.m_Parameters.m_NormMethodType = normMethod; |
| 167 | invalidData.m_Parameters.m_NormSize = normSize; |
| 168 | invalidData.m_Parameters.m_Alpha = alpha; |
| 169 | invalidData.m_Parameters.m_Beta = beta; |
| 170 | invalidData.m_Parameters.m_K = kappa; |
| 171 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 172 | //Invalid argument exception is expected, because input height != output height. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 173 | BOOST_CHECK_THROW(RefNormalizationFloat32Workload(invalidData, invalidInfo), armnn::InvalidArgumentException); |
| 174 | } |
| 175 | |
| 176 | BOOST_AUTO_TEST_CASE(SplitterQueueDescriptor_Validate_WrongWindow) |
| 177 | { |
| 178 | constexpr unsigned int inputNum = 1; |
| 179 | constexpr unsigned int inputHeight = 32; |
| 180 | constexpr unsigned int inputWidth = 24; |
| 181 | constexpr unsigned int inputChannels = 3; |
| 182 | |
| 183 | constexpr unsigned int outputNum = inputNum; |
| 184 | constexpr unsigned int outputChannels = inputChannels; |
| 185 | constexpr unsigned int outputHeight = 18; |
| 186 | constexpr unsigned int outputWidth = inputWidth; |
| 187 | |
| 188 | |
| 189 | armnn::TensorInfo inputTensorInfo; |
| 190 | armnn::TensorInfo outputTensorInfo; |
| 191 | |
| 192 | unsigned int inputShape[] = {inputNum, inputChannels, inputHeight, inputWidth}; |
| 193 | unsigned int outputShape[] = {outputNum, outputChannels, outputHeight, outputWidth}; |
| 194 | |
| 195 | inputTensorInfo = armnn::TensorInfo(4, inputShape, armnn::DataType::Float32); |
| 196 | outputTensorInfo = armnn::TensorInfo(4, outputShape, armnn::DataType::Float32); |
| 197 | |
| 198 | SplitterQueueDescriptor invalidData; |
| 199 | WorkloadInfo invalidInfo; |
| 200 | |
| 201 | AddInputToWorkload(invalidData, invalidInfo, inputTensorInfo, nullptr); |
| 202 | AddOutputToWorkload(invalidData, invalidInfo, outputTensorInfo, nullptr); |
| 203 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 204 | // Invalid, since it has only 3 dimensions while the input tensor is 4d. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 205 | std::vector<unsigned int> wOrigin = {0, 0, 0}; |
| 206 | armnn::SplitterQueueDescriptor::ViewOrigin window(wOrigin); |
| 207 | invalidData.m_ViewOrigins.push_back(window); |
| 208 | |
| 209 | BOOST_TEST_INFO("Invalid argument exception is expected, because split window dimensionality does not " |
| 210 | "match input."); |
| 211 | BOOST_CHECK_THROW(RefSplitterFloat32Workload(invalidData, invalidInfo), armnn::InvalidArgumentException); |
| 212 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 213 | // Invalid, since window extends past the boundary of input tensor. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 214 | std::vector<unsigned int> wOrigin3 = {0, 0, 15, 0}; |
| 215 | armnn::SplitterQueueDescriptor::ViewOrigin window3(wOrigin3); |
| 216 | invalidData.m_ViewOrigins[0] = window3; |
| 217 | BOOST_TEST_INFO("Invalid argument exception is expected (wOrigin3[2]+ outputHeight > inputHeight"); |
| 218 | BOOST_CHECK_THROW(RefSplitterFloat32Workload(invalidData, invalidInfo), armnn::InvalidArgumentException); |
| 219 | |
| 220 | |
| 221 | std::vector<unsigned int> wOrigin4 = {0, 0, 0, 0}; |
| 222 | armnn::SplitterQueueDescriptor::ViewOrigin window4(wOrigin4); |
| 223 | invalidData.m_ViewOrigins[0] = window4; |
| 224 | |
| 225 | std::vector<unsigned int> wOrigin5 = {1, 16, 20, 2}; |
| 226 | armnn::SplitterQueueDescriptor::ViewOrigin window5(wOrigin4); |
| 227 | invalidData.m_ViewOrigins.push_back(window5); |
| 228 | |
| 229 | BOOST_TEST_INFO("Invalid exception due to number of split windows not matching number of outputs."); |
| 230 | BOOST_CHECK_THROW(RefSplitterFloat32Workload(invalidData, invalidInfo), armnn::InvalidArgumentException); |
| 231 | } |
| 232 | |
| 233 | |
| 234 | BOOST_AUTO_TEST_CASE(MergerQueueDescriptor_Validate_WrongWindow) |
| 235 | { |
| 236 | constexpr unsigned int inputNum = 1; |
| 237 | constexpr unsigned int inputChannels = 3; |
| 238 | constexpr unsigned int inputHeight = 32; |
| 239 | constexpr unsigned int inputWidth = 24; |
| 240 | |
| 241 | constexpr unsigned int outputNum = 1; |
| 242 | constexpr unsigned int outputChannels = 3; |
| 243 | constexpr unsigned int outputHeight = 32; |
| 244 | constexpr unsigned int outputWidth = 24; |
| 245 | |
| 246 | |
| 247 | armnn::TensorInfo inputTensorInfo; |
| 248 | armnn::TensorInfo outputTensorInfo; |
| 249 | |
| 250 | unsigned int inputShape[] = {inputNum, inputChannels, inputHeight, inputWidth}; |
| 251 | unsigned int outputShape[] = {outputNum, outputChannels, outputHeight, outputWidth}; |
| 252 | |
| 253 | inputTensorInfo = armnn::TensorInfo(4, inputShape, armnn::DataType::Float32); |
| 254 | outputTensorInfo = armnn::TensorInfo(4, outputShape, armnn::DataType::Float32); |
| 255 | |
| 256 | MergerQueueDescriptor invalidData; |
| 257 | WorkloadInfo invalidInfo; |
| 258 | |
| 259 | AddInputToWorkload(invalidData, invalidInfo, inputTensorInfo, nullptr); |
| 260 | AddOutputToWorkload(invalidData, invalidInfo, outputTensorInfo, nullptr); |
| 261 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 262 | // Invalid, since it has only 3 dimensions while the input tensor is 4d. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 263 | std::vector<unsigned int> wOrigin = {0, 0, 0}; |
| 264 | armnn::MergerQueueDescriptor::ViewOrigin window(wOrigin); |
| 265 | invalidData.m_ViewOrigins.push_back(window); |
| 266 | |
| 267 | BOOST_TEST_INFO("Invalid argument exception is expected, because merge window dimensionality does not " |
| 268 | "match input."); |
| 269 | BOOST_CHECK_THROW(RefMergerFloat32Workload(invalidData, invalidInfo), armnn::InvalidArgumentException); |
| 270 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 271 | // Invalid, since window extends past the boundary of output tensor. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 272 | std::vector<unsigned int> wOrigin3 = {0, 0, 15, 0}; |
| 273 | armnn::MergerQueueDescriptor::ViewOrigin window3(wOrigin3); |
| 274 | invalidData.m_ViewOrigins[0] = window3; |
| 275 | BOOST_TEST_INFO("Invalid argument exception is expected (wOrigin3[2]+ inputHeight > outputHeight"); |
| 276 | BOOST_CHECK_THROW(RefMergerFloat32Workload(invalidData, invalidInfo), armnn::InvalidArgumentException); |
| 277 | |
| 278 | |
| 279 | std::vector<unsigned int> wOrigin4 = {0, 0, 0, 0}; |
| 280 | armnn::MergerQueueDescriptor::ViewOrigin window4(wOrigin4); |
| 281 | invalidData.m_ViewOrigins[0] = window4; |
| 282 | |
| 283 | std::vector<unsigned int> wOrigin5 = {1, 16, 20, 2}; |
| 284 | armnn::MergerQueueDescriptor::ViewOrigin window5(wOrigin4); |
| 285 | invalidData.m_ViewOrigins.push_back(window5); |
| 286 | |
| 287 | BOOST_TEST_INFO("Invalid exception due to number of merge windows not matching number of inputs."); |
| 288 | BOOST_CHECK_THROW(RefMergerFloat32Workload(invalidData, invalidInfo), armnn::InvalidArgumentException); |
| 289 | } |
| 290 | |
| 291 | BOOST_AUTO_TEST_CASE(AdditionQueueDescriptor_Validate_InputNumbers) |
| 292 | { |
| 293 | armnn::TensorInfo input1TensorInfo; |
| 294 | armnn::TensorInfo input2TensorInfo; |
| 295 | armnn::TensorInfo input3TensorInfo; |
| 296 | armnn::TensorInfo outputTensorInfo; |
| 297 | |
| 298 | unsigned int shape[] = {1, 1, 1, 1}; |
| 299 | |
| 300 | input1TensorInfo = armnn::TensorInfo(4, shape, armnn::DataType::Float32); |
| 301 | input2TensorInfo = armnn::TensorInfo(4, shape, armnn::DataType::Float32); |
| 302 | input3TensorInfo = armnn::TensorInfo(4, shape, armnn::DataType::Float32); |
| 303 | outputTensorInfo = armnn::TensorInfo(4, shape, armnn::DataType::Float32); |
| 304 | |
| 305 | AdditionQueueDescriptor invalidData; |
| 306 | WorkloadInfo invalidInfo; |
| 307 | |
| 308 | AddInputToWorkload(invalidData, invalidInfo, input1TensorInfo, nullptr); |
| 309 | AddOutputToWorkload(invalidData, invalidInfo, outputTensorInfo, nullptr); |
| 310 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 311 | // Too few inputs. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 312 | BOOST_CHECK_THROW(RefAdditionFloat32Workload(invalidData, invalidInfo), armnn::InvalidArgumentException); |
| 313 | |
| 314 | AddInputToWorkload(invalidData, invalidInfo, input2TensorInfo, nullptr); |
| 315 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 316 | // Correct. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 317 | BOOST_CHECK_NO_THROW(RefAdditionFloat32Workload(invalidData, invalidInfo)); |
| 318 | |
| 319 | AddInputToWorkload(invalidData, invalidInfo, input3TensorInfo, nullptr); |
| 320 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 321 | // Too many inputs. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 322 | BOOST_CHECK_THROW(RefAdditionFloat32Workload(invalidData, invalidInfo), armnn::InvalidArgumentException); |
| 323 | } |
| 324 | |
| 325 | BOOST_AUTO_TEST_CASE(AdditionQueueDescriptor_Validate_InputShapes) |
| 326 | { |
| 327 | armnn::TensorInfo input1TensorInfo; |
| 328 | armnn::TensorInfo input2TensorInfo; |
| 329 | armnn::TensorInfo outputTensorInfo; |
| 330 | |
| 331 | unsigned int shape1[] = {1, 1, 2, 1}; |
| 332 | unsigned int shape2[] = {1, 1, 3, 2}; |
| 333 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 334 | // Incompatible shapes even with broadcasting. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 335 | { |
| 336 | input1TensorInfo = armnn::TensorInfo(4, shape1, armnn::DataType::Float32); |
| 337 | input2TensorInfo = armnn::TensorInfo(4, shape2, armnn::DataType::Float32); |
| 338 | outputTensorInfo = armnn::TensorInfo(4, shape1, armnn::DataType::Float32); |
| 339 | |
| 340 | AdditionQueueDescriptor invalidData; |
| 341 | WorkloadInfo invalidInfo; |
| 342 | |
| 343 | AddInputToWorkload(invalidData, invalidInfo, input1TensorInfo, nullptr); |
| 344 | AddInputToWorkload(invalidData, invalidInfo, input2TensorInfo, nullptr); |
| 345 | AddOutputToWorkload(invalidData, invalidInfo, outputTensorInfo, nullptr); |
| 346 | |
| 347 | BOOST_CHECK_THROW(RefAdditionFloat32Workload(invalidData, invalidInfo), armnn::InvalidArgumentException); |
| 348 | } |
| 349 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 350 | // Output size not compatible with input sizes. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 351 | { |
| 352 | input1TensorInfo = armnn::TensorInfo(4, shape1, armnn::DataType::Float32); |
| 353 | input2TensorInfo = armnn::TensorInfo(4, shape1, armnn::DataType::Float32); |
| 354 | outputTensorInfo = armnn::TensorInfo(4, shape2, armnn::DataType::Float32); |
| 355 | |
| 356 | AdditionQueueDescriptor invalidData; |
| 357 | WorkloadInfo invalidInfo; |
| 358 | |
| 359 | AddInputToWorkload(invalidData, invalidInfo, input1TensorInfo, nullptr); |
| 360 | AddInputToWorkload(invalidData, invalidInfo, input2TensorInfo, nullptr); |
| 361 | AddOutputToWorkload(invalidData, invalidInfo, outputTensorInfo, nullptr); |
| 362 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 363 | // Output differs. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 364 | BOOST_CHECK_THROW(RefAdditionFloat32Workload(invalidData, invalidInfo), armnn::InvalidArgumentException); |
| 365 | } |
| 366 | } |
| 367 | |
| 368 | BOOST_AUTO_TEST_CASE(MultiplicationQueueDescriptor_Validate_InputTensorDimensionMismatch) |
| 369 | { |
| 370 | armnn::TensorInfo input0TensorInfo; |
| 371 | armnn::TensorInfo input1TensorInfo; |
| 372 | armnn::TensorInfo outputTensorInfo; |
| 373 | |
| 374 | constexpr unsigned int input0Shape[] = { 2, 2, 4, 4 }; |
| 375 | constexpr std::size_t dimensionCount = std::extent<decltype(input0Shape)>::value; |
| 376 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 377 | // Checks dimension consistency for input tensors. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 378 | for (unsigned int dimIndex = 0; dimIndex < dimensionCount; ++dimIndex) |
| 379 | { |
| 380 | unsigned int input1Shape[dimensionCount]; |
| 381 | for (unsigned int i = 0; i < dimensionCount; ++i) |
| 382 | { |
| 383 | input1Shape[i] = input0Shape[i]; |
| 384 | } |
| 385 | |
| 386 | ++input1Shape[dimIndex]; |
| 387 | |
| 388 | input0TensorInfo = armnn::TensorInfo(dimensionCount, input0Shape, armnn::DataType::Float32); |
| 389 | input1TensorInfo = armnn::TensorInfo(dimensionCount, input1Shape, armnn::DataType::Float32); |
| 390 | outputTensorInfo = armnn::TensorInfo(dimensionCount, input0Shape, armnn::DataType::Float32); |
| 391 | |
| 392 | MultiplicationQueueDescriptor invalidData; |
| 393 | WorkloadInfo invalidInfo; |
| 394 | |
| 395 | AddOutputToWorkload(invalidData, invalidInfo, outputTensorInfo, nullptr); |
| 396 | AddInputToWorkload(invalidData, invalidInfo, input0TensorInfo, nullptr); |
| 397 | AddInputToWorkload(invalidData, invalidInfo, input1TensorInfo, nullptr); |
| 398 | |
| 399 | BOOST_CHECK_THROW(RefMultiplicationFloat32Workload(invalidData, invalidInfo), armnn::InvalidArgumentException); |
| 400 | } |
| 401 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 402 | // Checks dimension consistency for input and output tensors. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 403 | for (unsigned int dimIndex = 0; dimIndex < dimensionCount; ++dimIndex) |
| 404 | { |
| 405 | unsigned int outputShape[dimensionCount]; |
| 406 | for (unsigned int i = 0; i < dimensionCount; ++i) |
| 407 | { |
| 408 | outputShape[i] = input0Shape[i]; |
| 409 | } |
| 410 | |
| 411 | ++outputShape[dimIndex]; |
| 412 | |
| 413 | input0TensorInfo = armnn::TensorInfo(dimensionCount, input0Shape, armnn::DataType::Float32); |
| 414 | input1TensorInfo = armnn::TensorInfo(dimensionCount, input0Shape, armnn::DataType::Float32); |
| 415 | outputTensorInfo = armnn::TensorInfo(dimensionCount, outputShape, armnn::DataType::Float32); |
| 416 | |
| 417 | MultiplicationQueueDescriptor invalidData; |
| 418 | WorkloadInfo invalidInfo; |
| 419 | |
| 420 | AddOutputToWorkload(invalidData, invalidInfo, outputTensorInfo, nullptr); |
| 421 | AddInputToWorkload(invalidData, invalidInfo, input0TensorInfo, nullptr); |
| 422 | AddInputToWorkload(invalidData, invalidInfo, input1TensorInfo, nullptr); |
| 423 | |
| 424 | BOOST_CHECK_THROW(RefMultiplicationFloat32Workload(invalidData, invalidInfo), armnn::InvalidArgumentException); |
| 425 | } |
| 426 | } |
| 427 | |
| 428 | BOOST_AUTO_TEST_CASE(ReshapeQueueDescriptor_Validate_MismatchingNumElements) |
| 429 | { |
| 430 | armnn::TensorInfo inputTensorInfo; |
| 431 | armnn::TensorInfo outputTensorInfo; |
| 432 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 433 | // The input and output shapes should have the same number of elements, but these don't. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 434 | unsigned int inputShape[] = { 1, 1, 2, 3 }; |
| 435 | unsigned int outputShape[] = { 1, 1, 1, 2 }; |
| 436 | |
| 437 | inputTensorInfo = armnn::TensorInfo(4, inputShape, armnn::DataType::Float32); |
| 438 | outputTensorInfo = armnn::TensorInfo(4, outputShape, armnn::DataType::Float32); |
| 439 | |
| 440 | ReshapeQueueDescriptor invalidData; |
| 441 | WorkloadInfo invalidInfo; |
| 442 | |
| 443 | AddInputToWorkload(invalidData, invalidInfo, inputTensorInfo, nullptr); |
| 444 | AddOutputToWorkload(invalidData, invalidInfo, outputTensorInfo, nullptr); |
| 445 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 446 | // InvalidArgumentException is expected, because the number of elements don't match. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 447 | BOOST_CHECK_THROW(RefReshapeFloat32Workload(invalidData, invalidInfo), armnn::InvalidArgumentException); |
| 448 | } |
| 449 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 450 | |
| 451 | BOOST_AUTO_TEST_CASE(LstmQueueDescriptor_Validate) |
| 452 | { |
| 453 | armnn::TensorInfo inputTensorInfo; |
| 454 | armnn::TensorInfo outputTensorInfo; |
| 455 | |
| 456 | unsigned int inputShape[] = { 1, 2 }; |
| 457 | unsigned int outputShape[] = { 1 }; |
| 458 | |
| 459 | inputTensorInfo = armnn::TensorInfo(2, inputShape, armnn::DataType::Float32); |
| 460 | outputTensorInfo = armnn::TensorInfo(1, outputShape, armnn::DataType::Float32); |
| 461 | |
| 462 | LstmQueueDescriptor invalidData; |
| 463 | WorkloadInfo invalidInfo; |
| 464 | |
| 465 | AddInputToWorkload(invalidData, invalidInfo, inputTensorInfo, nullptr); |
| 466 | AddOutputToWorkload(invalidData, invalidInfo, outputTensorInfo, nullptr); |
| 467 | |
| 468 | BOOST_CHECK_THROW(invalidData.Validate(invalidInfo), armnn::InvalidArgumentException); |
| 469 | } |
| 470 | |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 471 | BOOST_AUTO_TEST_SUITE_END() |