Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 1 | // |
| 2 | // Copyright © 2021 Arm Ltd and Contributors. All rights reserved. |
| 3 | // SPDX-License-Identifier: MIT |
| 4 | // |
| 5 | |
| 6 | |
| 7 | #include "Pooling3dTestImpl.hpp" |
| 8 | |
Colm Donelan | c42a987 | 2022-02-02 16:35:09 +0000 | [diff] [blame] | 9 | #include <armnnUtils/QuantizeHelper.hpp> |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 10 | #include <ResolveType.hpp> |
| 11 | |
| 12 | #include <armnnUtils/TensorUtils.hpp> |
| 13 | #include <armnnUtils/DataLayoutIndexed.hpp> |
| 14 | #include <armnnUtils/Permute.hpp> |
| 15 | |
| 16 | #include <armnn/utility/IgnoreUnused.hpp> |
| 17 | #include <armnn/utility/NumericCast.hpp> |
| 18 | |
| 19 | #include <armnn/BackendHelper.hpp> |
| 20 | #include <backendsCommon/WorkloadInfo.hpp> |
| 21 | |
Sadik Armagan | a097d2a | 2021-11-24 15:47:28 +0000 | [diff] [blame] | 22 | #include <armnnTestUtils/TensorCopyUtils.hpp> |
Colm Donelan | 0c47974 | 2021-12-10 12:43:54 +0000 | [diff] [blame] | 23 | #include <armnnTestUtils/WorkloadTestUtils.hpp> |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 24 | |
Colm Donelan | c42a987 | 2022-02-02 16:35:09 +0000 | [diff] [blame] | 25 | #include <armnnTestUtils/TensorHelpers.hpp> |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 26 | |
| 27 | namespace |
| 28 | { |
| 29 | |
| 30 | using namespace armnnUtils; |
| 31 | |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 32 | template<typename T> |
| 33 | void PermuteNCDHWToNDHWC(std::vector<T> &src, armnn::TensorInfo &srcInfo) |
| 34 | { |
| 35 | const armnn::PermutationVector NCDHWToNDHWC = { 0, 4, 1, 2, 3 }; |
| 36 | std::vector<T> tmp(src.size()); |
| 37 | armnnUtils::Permute(srcInfo.GetShape(), NCDHWToNDHWC, src.data(), tmp.data(), sizeof(T)); |
| 38 | src = tmp; |
| 39 | } |
| 40 | |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 41 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
| 42 | LayerTestResult<T, 5> SimplePooling3dTestImpl( |
| 43 | armnn::IWorkloadFactory& workloadFactory, |
| 44 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 45 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
| 46 | armnn::Pooling3dDescriptor descriptor, |
| 47 | float qScale, |
| 48 | int32_t qOffset, |
| 49 | const std::vector<T>& input, |
| 50 | const std::vector<T>& outputExpected, |
| 51 | const armnn::TensorShape& inputShape, |
| 52 | const armnn::TensorShape& outputShape) |
| 53 | { |
| 54 | IgnoreUnused(memoryManager); |
| 55 | const armnn::DataLayout dataLayout = descriptor.m_DataLayout; |
| 56 | const armnnUtils::DataLayoutIndexed dimensionIndices = dataLayout; |
| 57 | auto heightIndex = dimensionIndices.GetHeightIndex(); |
| 58 | auto widthIndex = dimensionIndices.GetWidthIndex(); |
| 59 | auto depthIndex = dimensionIndices.GetDepthIndex(); |
| 60 | auto channelsIndex = dimensionIndices.GetChannelsIndex(); |
| 61 | |
| 62 | unsigned int inputDepth = armnn::numeric_cast<unsigned int>(inputShape[depthIndex]); |
| 63 | unsigned int inputHeight = armnn::numeric_cast<unsigned int>(inputShape[heightIndex]); |
| 64 | unsigned int inputWidth = armnn::numeric_cast<unsigned int>(inputShape[widthIndex]); |
| 65 | unsigned int inputChannels = armnn::numeric_cast<unsigned int>(inputShape[channelsIndex]); |
| 66 | unsigned int inputBatchSize = armnn::numeric_cast<unsigned int>(inputShape[0]); |
| 67 | |
| 68 | unsigned int outputDepth = armnn::numeric_cast<unsigned int>(outputShape[depthIndex]); |
| 69 | unsigned int outputHeight = armnn::numeric_cast<unsigned int>(outputShape[heightIndex]); |
| 70 | unsigned int outputWidth = armnn::numeric_cast<unsigned int>(outputShape[widthIndex]); |
| 71 | unsigned int outputChannels = armnn::numeric_cast<unsigned int>(outputShape[channelsIndex]); |
| 72 | unsigned int outputBatchSize = armnn::numeric_cast<unsigned int>(outputShape[0]); |
| 73 | |
| 74 | armnn::TensorInfo inputTensorInfo = armnnUtils::GetTensorInfo( |
| 75 | inputBatchSize, inputChannels, inputDepth, inputHeight, inputWidth, dataLayout, ArmnnType); |
| 76 | |
| 77 | armnn::TensorInfo outputTensorInfo = armnnUtils::GetTensorInfo( |
| 78 | outputBatchSize, outputChannels, outputDepth, outputHeight, outputWidth, dataLayout, ArmnnType); |
| 79 | |
| 80 | // Set quantization parameters if the requested type is a quantized type. |
| 81 | if (armnn::IsQuantizedType<T>()) |
| 82 | { |
| 83 | inputTensorInfo.SetQuantizationScale(qScale); |
| 84 | inputTensorInfo.SetQuantizationOffset(qOffset); |
| 85 | outputTensorInfo.SetQuantizationScale(qScale); |
| 86 | outputTensorInfo.SetQuantizationOffset(qOffset); |
| 87 | } |
| 88 | |
| 89 | LayerTestResult<T, 5> result(outputTensorInfo); |
| 90 | std::vector<T> actualOutput(outputTensorInfo.GetNumElements()); |
| 91 | |
| 92 | std::unique_ptr<armnn::ITensorHandle> inputHandle = tensorHandleFactory.CreateTensorHandle(inputTensorInfo); |
| 93 | std::unique_ptr<armnn::ITensorHandle> outputHandle = tensorHandleFactory.CreateTensorHandle(outputTensorInfo); |
| 94 | |
| 95 | armnn::Pooling3dQueueDescriptor queueDescriptor; |
| 96 | queueDescriptor.m_Parameters = descriptor; |
| 97 | queueDescriptor.m_Parameters.m_DataLayout = dataLayout; |
| 98 | |
| 99 | armnn::WorkloadInfo workloadInfo; |
| 100 | AddInputToWorkload(queueDescriptor, workloadInfo, inputTensorInfo, inputHandle.get()); |
| 101 | AddOutputToWorkload(queueDescriptor, workloadInfo, outputTensorInfo, outputHandle.get()); |
| 102 | |
| 103 | // Don't execute if Pooling is not supported, as an exception will be raised. |
| 104 | armnn::BackendId backend = workloadFactory.GetBackendId(); |
| 105 | std::string reasonIfUnsupported; |
| 106 | armnn::LayerSupportHandle handle = armnn::GetILayerSupportByBackendId(backend); |
| 107 | result.m_Supported = handle.IsPooling3dSupported(inputTensorInfo, |
| 108 | outputTensorInfo, |
| 109 | queueDescriptor.m_Parameters, |
| 110 | reasonIfUnsupported); |
| 111 | if (!result.m_Supported) |
| 112 | { |
| 113 | return result; |
| 114 | } |
| 115 | |
Teresa Charlin | 611c7fb | 2022-01-07 09:47:29 +0000 | [diff] [blame] | 116 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateWorkload(armnn::LayerType::Pooling3d, |
| 117 | queueDescriptor, |
| 118 | workloadInfo); |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 119 | |
| 120 | inputHandle->Allocate(); |
| 121 | outputHandle->Allocate(); |
| 122 | |
| 123 | CopyDataToITensorHandle(inputHandle.get(), input.data()); |
| 124 | |
| 125 | workload->Execute(); |
| 126 | |
| 127 | CopyDataFromITensorHandle(actualOutput.data(), outputHandle.get()); |
| 128 | |
| 129 | result.m_ActualData = actualOutput; |
| 130 | result.m_ExpectedData = outputExpected; |
| 131 | |
| 132 | return result; |
| 133 | } |
| 134 | |
| 135 | // |
| 136 | // Tests max pooling with the following parameters: |
| 137 | // |
| 138 | // Pooling size: 2x2x2 |
| 139 | // Stride: (1,1,1) |
| 140 | // input size: 3x3x3 |
| 141 | // channels: 2 |
| 142 | // batch size: 2 |
| 143 | // |
| 144 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
| 145 | LayerTestResult<T, 5> SimpleMaxPooling3dSize2x2x2Stride1x1x1TestCommon( |
| 146 | armnn::IWorkloadFactory& workloadFactory, |
| 147 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 148 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 149 | const armnn::DataLayout dataLayout, |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 150 | float qScale = 1.0f, |
| 151 | int32_t qOffset = 0) |
| 152 | { |
| 153 | armnn::Pooling3dDescriptor descriptor; |
| 154 | descriptor.m_PoolType = armnn::PoolingAlgorithm::Max; |
| 155 | descriptor.m_PoolWidth = 2; |
| 156 | descriptor.m_PoolHeight = 2; |
| 157 | descriptor.m_PoolDepth = 2; |
| 158 | descriptor.m_StrideX = 1; |
| 159 | descriptor.m_StrideY = 1; |
| 160 | descriptor.m_StrideZ = 1; |
| 161 | descriptor.m_PadLeft = descriptor.m_PadRight = 0; |
| 162 | descriptor.m_PadTop = descriptor.m_PadBottom = 0; |
| 163 | descriptor.m_PadFront = descriptor.m_PadBack = 0; |
| 164 | descriptor.m_OutputShapeRounding = armnn::OutputShapeRounding::Floor; |
| 165 | descriptor.m_PaddingMethod = armnn::PaddingMethod::Exclude; |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 166 | descriptor.m_DataLayout = dataLayout; |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 167 | |
| 168 | unsigned int inputWidth = 3; |
| 169 | unsigned int inputHeight = 3; |
| 170 | unsigned int inputDepth = 3; |
| 171 | unsigned int outputWidth = |
| 172 | (inputWidth + descriptor.m_PadLeft + descriptor.m_PadRight + descriptor.m_StrideX - descriptor.m_PoolWidth) / |
| 173 | descriptor.m_StrideX; |
| 174 | unsigned int outputHeight = |
| 175 | (inputHeight + descriptor.m_PadTop + descriptor.m_PadBottom + descriptor.m_StrideY - descriptor.m_PoolHeight) / |
| 176 | descriptor.m_StrideY; |
| 177 | unsigned int outputDepth = |
| 178 | (inputDepth + descriptor.m_PadFront + descriptor.m_PadBack + descriptor.m_StrideZ - descriptor.m_PoolDepth) / |
| 179 | descriptor.m_StrideZ; |
| 180 | unsigned int channels = 2; |
| 181 | unsigned int batchSize = 2; |
| 182 | |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 183 | armnn::TensorInfo inputTensorInfo = armnnUtils::GetTensorInfo( batchSize, channels, inputDepth, inputHeight, |
| 184 | inputWidth, dataLayout, ArmnnType); |
| 185 | armnn::TensorInfo outputTensorInfo = armnnUtils::GetTensorInfo( batchSize, channels, outputDepth, outputHeight, |
| 186 | outputWidth, dataLayout, ArmnnType); |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 187 | |
| 188 | // Set quantization parameters if the requested type is a quantized type. |
| 189 | if(armnn::IsQuantizedType<T>()) |
| 190 | { |
| 191 | inputTensorInfo.SetQuantizationScale(qScale); |
| 192 | inputTensorInfo.SetQuantizationOffset(qOffset); |
| 193 | outputTensorInfo.SetQuantizationScale(qScale); |
| 194 | outputTensorInfo.SetQuantizationOffset(qOffset); |
| 195 | } |
| 196 | |
| 197 | std::vector<float> singleChannelData({ |
| 198 | 1.0f, 1.0f, 1.0f, |
| 199 | 1.0f, 1.0f, 1.0f, |
| 200 | 1.0f, 1.0f, 1.0f, |
| 201 | |
| 202 | 1.0f, 1.0f, 1.0f, |
| 203 | 1.0f, 1.0f, 1.0f, |
| 204 | 1.0f, 1.0f, 1.0f, |
| 205 | |
| 206 | 1.0f, 1.0f, 1.0f, |
| 207 | 1.0f, 1.0f, 1.0f, |
| 208 | 1.0f, 1.0f, 1.0f, |
| 209 | }); |
| 210 | |
| 211 | // Constructs input data. |
| 212 | std::vector<float> inputData; |
| 213 | auto negator = [](float f) { return -f; }; |
| 214 | |
| 215 | // First image (two channels where the second channel is the negative of the first one). |
| 216 | inputData.insert(inputData.end(), singleChannelData.begin(), singleChannelData.end()); |
| 217 | std::transform(singleChannelData.begin(), singleChannelData.end(), std::back_inserter(inputData), negator); |
| 218 | |
| 219 | // Second image (same as first image). |
| 220 | inputData.insert(inputData.end(), singleChannelData.begin(), singleChannelData.end()); |
| 221 | std::transform(singleChannelData.begin(), singleChannelData.end(), std::back_inserter(inputData), negator); |
| 222 | |
| 223 | auto input = QuantizedVector<T>(inputData, qScale, qOffset); |
| 224 | |
| 225 | // These were calculated manually. |
| 226 | std::vector<T> outputExpected = QuantizedVector<T>( |
| 227 | { |
| 228 | 1.0f, 1.0f, |
| 229 | 1.0f, 1.0f, |
| 230 | |
| 231 | 1.0f, 1.0f, |
| 232 | 1.0f, 1.0f, |
| 233 | |
| 234 | -1.0f, -1.0f, |
| 235 | -1.0f, -1.0f, |
| 236 | |
| 237 | -1.0f, -1.0f, |
| 238 | -1.0f, -1.0f, |
| 239 | |
| 240 | |
| 241 | 1.0f, 1.0f, |
| 242 | 1.0f, 1.0f, |
| 243 | |
| 244 | 1.0f, 1.0f, |
| 245 | 1.0f, 1.0f, |
| 246 | |
| 247 | -1.0f, -1.0f, |
| 248 | -1.0f, -1.0f, |
| 249 | |
| 250 | -1.0f, -1.0f, |
| 251 | -1.0f, -1.0f, |
| 252 | }, |
| 253 | qScale, qOffset); |
| 254 | |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 255 | if (dataLayout == armnn::DataLayout::NDHWC) |
| 256 | { |
| 257 | PermuteNCDHWToNDHWC(input, inputTensorInfo); |
| 258 | PermuteNCDHWToNDHWC(outputExpected, outputTensorInfo); |
| 259 | } |
| 260 | |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 261 | return SimplePooling3dTestImpl<ArmnnType>( |
| 262 | workloadFactory, memoryManager, tensorHandleFactory, descriptor, qScale, qOffset, |
| 263 | input, outputExpected, inputTensorInfo.GetShape(), outputTensorInfo.GetShape()); |
| 264 | } |
| 265 | |
| 266 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
| 267 | LayerTestResult<T, 5> SimpleMaxPooling3dTestCommon( |
| 268 | armnn::IWorkloadFactory& workloadFactory, |
| 269 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 270 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 271 | const armnn::DataLayout dataLayout, |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 272 | float qScale = 1.0f, |
| 273 | int32_t qOffset = 0) |
| 274 | { |
| 275 | armnn::Pooling3dDescriptor descriptor; |
| 276 | descriptor.m_PoolType = armnn::PoolingAlgorithm::Max; |
| 277 | descriptor.m_PoolWidth = descriptor.m_PoolHeight = descriptor.m_PoolDepth = 2; |
| 278 | descriptor.m_StrideX = descriptor.m_StrideY = descriptor.m_StrideZ = 2; |
| 279 | descriptor.m_PaddingMethod = armnn::PaddingMethod::Exclude; |
| 280 | descriptor.m_DataLayout = dataLayout; |
| 281 | |
| 282 | armnn::TensorInfo inputTensorInfo = armnnUtils::GetTensorInfo(1, 1, 4, 4, 4, dataLayout, ArmnnType); |
| 283 | armnn::TensorInfo outputTensorInfo = armnnUtils::GetTensorInfo(1, 1, 2, 2, 2, dataLayout, ArmnnType); |
| 284 | |
| 285 | // Set quantization parameters if the requested type is a quantized type. |
| 286 | if(armnn::IsQuantizedType<T>()) |
| 287 | { |
| 288 | inputTensorInfo.SetQuantizationScale(qScale); |
| 289 | inputTensorInfo.SetQuantizationOffset(qOffset); |
| 290 | outputTensorInfo.SetQuantizationScale(qScale); |
| 291 | outputTensorInfo.SetQuantizationOffset(qOffset); |
| 292 | } |
| 293 | |
| 294 | std::vector<T> inputData( |
| 295 | QuantizedVector<T>({ |
| 296 | 1.0f, 2.0f, 5.0f, 6.0f, |
| 297 | 3.0f, 4.0f, 7.0f, 8.0f, |
| 298 | 9.0f, 10.0f, 13.0f, 14.0f, |
| 299 | 11.0f, 12.0f, 15.0f, 16.0f, |
| 300 | |
| 301 | 17.0f, 18.0f, 21.0f, 22.0f, |
| 302 | 19.0f, 20.0f, 23.0f, 24.0f, |
| 303 | 25.0f, 26.0f, 29.0f, 30.0f, |
| 304 | 27.0f, 28.0f, 31.0f, 32.0f, |
| 305 | |
| 306 | 33.0f, 34.0f, 37.0f, 38.0f, |
| 307 | 35.0f, 36.0f, 39.0f, 40.0f, |
| 308 | 41.0f, 42.0f, 45.0f, 46.0f, |
| 309 | 43.0f, 44.0f, 47.0f, 48.0f, |
| 310 | |
| 311 | 49.0f, 50.0f, 53.0f, 54.0f, |
| 312 | 51.0f, 52.0f, 55.0f, 56.0f, |
| 313 | 57.0f, 58.0f, 61.0f, 62.0f, |
| 314 | 59.0f, 60.0f, 63.0f, 64.0f, |
| 315 | }, |
| 316 | qScale, qOffset)); |
| 317 | |
| 318 | std::vector<T> outputData( |
| 319 | QuantizedVector<T>({ |
| 320 | 20.0f, 24.0f, |
| 321 | 28.0f, 32.0f, |
| 322 | |
| 323 | 52.0f, 56.0f, |
| 324 | 60.0f, 64.0f, |
| 325 | }, |
| 326 | qScale, qOffset)); |
| 327 | |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 328 | if (dataLayout == armnn::DataLayout::NDHWC) |
| 329 | { |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 330 | PermuteNCDHWToNDHWC(inputData, inputTensorInfo); |
| 331 | PermuteNCDHWToNDHWC(outputData, outputTensorInfo); |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 332 | } |
| 333 | |
| 334 | return SimplePooling3dTestImpl<ArmnnType>( |
| 335 | workloadFactory, memoryManager, tensorHandleFactory, descriptor, qScale, qOffset, |
| 336 | inputData, outputData, inputTensorInfo.GetShape(), outputTensorInfo.GetShape()); |
| 337 | } |
| 338 | |
| 339 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
| 340 | LayerTestResult<T, 5> IgnorePaddingSimpleMaxPooling3dTestCommon( |
| 341 | armnn::IWorkloadFactory& workloadFactory, |
| 342 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 343 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 344 | const armnn::DataLayout dataLayout, |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 345 | float qScale = 1.0f, |
| 346 | int32_t qOffset = 0) |
| 347 | { |
| 348 | armnn::Pooling3dDescriptor descriptor; |
| 349 | descriptor.m_PoolType = armnn::PoolingAlgorithm::Max; |
| 350 | descriptor.m_PoolWidth = descriptor.m_PoolHeight = descriptor.m_PoolDepth = 2; |
| 351 | descriptor.m_StrideX = descriptor.m_StrideY = descriptor.m_StrideZ = 2; |
| 352 | descriptor.m_PadLeft = 1; |
| 353 | descriptor.m_PadRight = 1; |
| 354 | descriptor.m_PadTop = 1; |
| 355 | descriptor.m_PadBottom = 1; |
| 356 | descriptor.m_PadFront = 1; |
| 357 | descriptor.m_PadBack = 1; |
| 358 | descriptor.m_PaddingMethod = armnn::PaddingMethod::IgnoreValue; |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 359 | descriptor.m_DataLayout = dataLayout; |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 360 | |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 361 | armnn::TensorInfo inputTensorInfo = armnnUtils::GetTensorInfo( 1, 1, 4, 4, 4 , dataLayout, ArmnnType); |
| 362 | armnn::TensorInfo outputTensorInfo = armnnUtils::GetTensorInfo( 1, 1, 3, 3, 3 , dataLayout, ArmnnType); |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 363 | |
| 364 | // Set quantization parameters if the requested type is a quantized type. |
| 365 | if(armnn::IsQuantizedType<T>()) |
| 366 | { |
| 367 | inputTensorInfo.SetQuantizationScale(qScale); |
| 368 | inputTensorInfo.SetQuantizationOffset(qOffset); |
| 369 | outputTensorInfo.SetQuantizationScale(qScale); |
| 370 | outputTensorInfo.SetQuantizationOffset(qOffset); |
| 371 | } |
| 372 | |
| 373 | auto input = QuantizedVector<T>( |
| 374 | { |
| 375 | -1.0f, -2.0f, 3.0f, 4.0f, |
| 376 | -1.0f, -2.0f, 3.0f, 4.0f, |
| 377 | 1.0f, 2.0f, -3.0f, -4.0f, |
| 378 | 1.0f, 2.0f, -3.0f, -4.0f, |
| 379 | |
| 380 | -1.0f, -2.0f, 3.0f, 4.0f, |
| 381 | -1.0f, -2.0f, 3.0f, 4.0f, |
| 382 | 1.0f, 2.0f, -3.0f, -4.0f, |
| 383 | 1.0f, 2.0f, -3.0f, -4.0f, |
| 384 | |
| 385 | -1.0f, -2.0f, 3.0f, 4.0f, |
| 386 | -1.0f, -2.0f, 3.0f, 4.0f, |
| 387 | 1.0f, 2.0f, -3.0f, -4.0f, |
| 388 | 1.0f, 2.0f, -3.0f, -4.0f, |
| 389 | |
| 390 | -1.0f, -2.0f, 3.0f, 4.0f, |
| 391 | -1.0f, -2.0f, 3.0f, 4.0f, |
| 392 | 1.0f, 2.0f, -3.0f, -4.0f, |
| 393 | 1.0f, 2.0f, -3.0f, -4.0f, |
| 394 | }, |
| 395 | qScale, qOffset); |
| 396 | |
| 397 | auto outputExpected = QuantizedVector<T>( |
| 398 | { |
| 399 | -1.0f, 3.0f, 4.0f, |
| 400 | 1.0f, 3.0f, 4.0f, |
| 401 | 1.0f, 2.0f, -4.0f, |
| 402 | |
| 403 | -1.0f, 3.0f, 4.0f, |
| 404 | 1.0f, 3.0f, 4.0f, |
| 405 | 1.0f, 2.0f, -4.0f, |
| 406 | |
| 407 | -1.0f, 3.0f, 4.0f, |
| 408 | 1.0f, 3.0f, 4.0f, |
| 409 | 1.0f, 2.0f, -4.0f, |
| 410 | }, |
| 411 | qScale, qOffset); |
| 412 | |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 413 | if (dataLayout == armnn::DataLayout::NDHWC) |
| 414 | { |
| 415 | PermuteNCDHWToNDHWC(input, inputTensorInfo); |
| 416 | PermuteNCDHWToNDHWC(outputExpected, outputTensorInfo); |
| 417 | } |
| 418 | |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 419 | return SimplePooling3dTestImpl<ArmnnType>( |
| 420 | workloadFactory, memoryManager, tensorHandleFactory, descriptor, qScale, qOffset, |
| 421 | input, outputExpected, inputTensorInfo.GetShape(), outputTensorInfo.GetShape()); |
| 422 | } |
| 423 | |
| 424 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
| 425 | LayerTestResult<T, 5> SimpleAveragePooling3dTestCommon( |
| 426 | armnn::IWorkloadFactory& workloadFactory, |
| 427 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 428 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
| 429 | armnn::DataLayout dataLayout = armnn::DataLayout::NCDHW, |
| 430 | float qScale = 1.0f, |
| 431 | int32_t qOffset = 0) |
| 432 | { |
| 433 | armnn::Pooling3dDescriptor descriptor; |
| 434 | descriptor.m_PoolType = armnn::PoolingAlgorithm::Average; |
| 435 | descriptor.m_PoolWidth = descriptor.m_PoolHeight = descriptor.m_PoolDepth = 2; |
| 436 | descriptor.m_StrideX = descriptor.m_StrideY = descriptor.m_StrideZ = 2; |
| 437 | descriptor.m_PaddingMethod = armnn::PaddingMethod::Exclude; |
| 438 | descriptor.m_DataLayout = dataLayout; |
| 439 | |
| 440 | armnn::TensorInfo inputTensorInfo = armnnUtils::GetTensorInfo(1, 1, 4, 4, 4, dataLayout, ArmnnType); |
| 441 | armnn::TensorInfo outputTensorInfo = armnnUtils::GetTensorInfo(1, 1, 2, 2, 2, dataLayout, ArmnnType); |
| 442 | |
| 443 | // Set quantization parameters if the requested type is a quantized type. |
| 444 | if(armnn::IsQuantizedType<T>()) |
| 445 | { |
| 446 | inputTensorInfo.SetQuantizationScale(qScale); |
| 447 | inputTensorInfo.SetQuantizationOffset(qOffset); |
| 448 | outputTensorInfo.SetQuantizationScale(qScale); |
| 449 | outputTensorInfo.SetQuantizationOffset(qOffset); |
| 450 | } |
| 451 | |
| 452 | std::vector<T> inputData( |
| 453 | QuantizedVector<T>({ |
| 454 | 1.0f, 2.0f, 5.0f, 6.0f, |
| 455 | 3.0f, 4.0f, 7.0f, 8.0f, |
| 456 | 9.0f, 10.0f, 13.0f, 14.0f, |
| 457 | 11.0f, 12.0f, 15.0f, 16.0f, |
| 458 | |
| 459 | 17.0f, 18.0f, 21.0f, 22.0f, |
| 460 | 19.0f, 20.0f, 23.0f, 24.0f, |
| 461 | 25.0f, 26.0f, 29.0f, 30.0f, |
| 462 | 27.0f, 28.0f, 31.0f, 32.0f, |
| 463 | |
| 464 | 33.0f, 34.0f, 37.0f, 38.0f, |
| 465 | 35.0f, 36.0f, 39.0f, 40.0f, |
| 466 | 41.0f, 42.0f, 45.0f, 46.0f, |
| 467 | 43.0f, 44.0f, 47.0f, 48.0f, |
| 468 | |
| 469 | 49.0f, 50.0f, 53.0f, 54.0f, |
| 470 | 51.0f, 52.0f, 55.0f, 56.0f, |
| 471 | 57.0f, 58.0f, 61.0f, 62.0f, |
| 472 | 59.0f, 60.0f, 63.0f, 64.0f, |
| 473 | }, |
| 474 | qScale, qOffset)); |
| 475 | |
| 476 | std::vector<T> outputData( |
| 477 | QuantizedVector<T>({ |
| 478 | 10.5f, 14.5f, |
| 479 | 18.5f, 22.5f, |
| 480 | |
| 481 | 42.5f, 46.5f, |
| 482 | 50.5f, 54.5f, |
| 483 | }, |
| 484 | qScale, qOffset)); |
| 485 | |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 486 | if (dataLayout == armnn::DataLayout::NDHWC) |
| 487 | { |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 488 | PermuteNCDHWToNDHWC(inputData, inputTensorInfo); |
| 489 | PermuteNCDHWToNDHWC(outputData, outputTensorInfo); |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 490 | } |
| 491 | |
| 492 | return SimplePooling3dTestImpl<ArmnnType>( |
| 493 | workloadFactory, memoryManager, tensorHandleFactory, descriptor, qScale, qOffset, |
| 494 | inputData, outputData, inputTensorInfo.GetShape(), outputTensorInfo.GetShape()); |
| 495 | } |
| 496 | |
| 497 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
| 498 | LayerTestResult<T, 5> LargeTensorsAveragePooling3dTestCommon( |
| 499 | armnn::IWorkloadFactory& workloadFactory, |
| 500 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 501 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 502 | const armnn::DataLayout dataLayout, |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 503 | float qScale = 1.0f, |
| 504 | int32_t qOffset = 0) |
| 505 | { |
| 506 | armnn::Pooling3dDescriptor descriptor; |
| 507 | descriptor.m_PoolType = armnn::PoolingAlgorithm::Average; |
| 508 | descriptor.m_PoolWidth = descriptor.m_PoolHeight = descriptor.m_PoolDepth = 100; |
| 509 | descriptor.m_StrideX = descriptor.m_StrideY = descriptor.m_StrideZ = 5; |
| 510 | descriptor.m_PadLeft = 50; |
| 511 | descriptor.m_PadRight = 50; |
| 512 | descriptor.m_PadTop = 50; |
| 513 | descriptor.m_PadBottom = 50; |
| 514 | descriptor.m_PadFront = 50; |
| 515 | descriptor.m_PadBack = 50; |
| 516 | descriptor.m_PaddingMethod = armnn::PaddingMethod::Exclude; |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 517 | descriptor.m_DataLayout = dataLayout; |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 518 | |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 519 | armnn::TensorInfo inputTensorInfo = armnnUtils::GetTensorInfo( 5, 3, 52, 60, 68, dataLayout, ArmnnType); |
| 520 | armnn::TensorInfo outputTensorInfo = armnnUtils::GetTensorInfo( 5, 3, 11, 13, 14, dataLayout, ArmnnType); |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 521 | |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 522 | // Set quantization parameters if the requested type is a quantized type.armnnUtils::GetTensorInfo( |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 523 | if(armnn::IsQuantizedType<T>()) |
| 524 | { |
| 525 | inputTensorInfo.SetQuantizationScale(qScale); |
| 526 | inputTensorInfo.SetQuantizationOffset(qOffset); |
| 527 | outputTensorInfo.SetQuantizationScale(qScale); |
| 528 | outputTensorInfo.SetQuantizationOffset(qOffset); |
| 529 | } |
| 530 | |
| 531 | std::vector<T> input; |
| 532 | |
| 533 | for (unsigned int i = 0 ; i < inputTensorInfo.GetShape().GetNumElements(); ++i) |
| 534 | { |
| 535 | input.push_back(1); |
| 536 | } |
| 537 | |
| 538 | std::vector<T> outputExpected; |
| 539 | |
| 540 | for (unsigned int i = 0 ; i < outputTensorInfo.GetShape().GetNumElements(); ++i) |
| 541 | { |
| 542 | outputExpected.push_back(1); |
| 543 | } |
| 544 | |
| 545 | return SimplePooling3dTestImpl<ArmnnType>( |
| 546 | workloadFactory, memoryManager, tensorHandleFactory, descriptor, qScale, qOffset, |
| 547 | input, outputExpected, inputTensorInfo.GetShape(), outputTensorInfo.GetShape()); |
| 548 | } |
| 549 | |
| 550 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
| 551 | LayerTestResult<T, 5> IgnorePaddingSimpleAveragePooling3dTestCommon( |
| 552 | armnn::IWorkloadFactory& workloadFactory, |
| 553 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 554 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 555 | const armnn::DataLayout dataLayout, |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 556 | float qScale = 1.0f, |
| 557 | int32_t qOffset = 0) |
| 558 | { |
| 559 | armnn::Pooling3dDescriptor descriptor; |
| 560 | descriptor.m_PoolType = armnn::PoolingAlgorithm::Average; |
| 561 | descriptor.m_PoolWidth = descriptor.m_PoolHeight = descriptor.m_PoolDepth = 2; |
| 562 | descriptor.m_StrideX = descriptor.m_StrideY = descriptor.m_StrideZ = 2; |
| 563 | descriptor.m_PadLeft = 1; |
| 564 | descriptor.m_PadRight = 1; |
| 565 | descriptor.m_PadTop = 1; |
| 566 | descriptor.m_PadBottom = 1; |
| 567 | descriptor.m_PadFront = 1; |
| 568 | descriptor.m_PadBack = 1; |
| 569 | descriptor.m_PaddingMethod = armnn::PaddingMethod::IgnoreValue; |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 570 | descriptor.m_DataLayout = dataLayout; |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 571 | |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 572 | |
| 573 | armnn::TensorInfo inputTensorInfo = armnnUtils::GetTensorInfo ( 1, 1, 4, 4, 4, dataLayout, ArmnnType); |
| 574 | armnn::TensorInfo outputTensorInfo = armnnUtils::GetTensorInfo( 1, 1, 3, 3, 3, dataLayout, ArmnnType); |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 575 | |
| 576 | // Set quantization parameters if the requested type is a quantized type. |
| 577 | if(armnn::IsQuantizedType<T>()) |
| 578 | { |
| 579 | inputTensorInfo.SetQuantizationScale(qScale); |
| 580 | inputTensorInfo.SetQuantizationOffset(qOffset); |
| 581 | outputTensorInfo.SetQuantizationScale(qScale); |
| 582 | outputTensorInfo.SetQuantizationOffset(qOffset); |
| 583 | } |
| 584 | |
| 585 | auto input = QuantizedVector<T>( |
| 586 | { |
| 587 | 12.0f, 20.0f, 32.0f, 40.0f, |
| 588 | 12.0f, 20.0f, 32.0f, 40.0f, |
| 589 | 12.0f, 20.0f, 32.0f, 40.0f, |
| 590 | 12.0f, 20.0f, 32.0f, 40.0f, |
| 591 | |
| 592 | 24.0f, 40.0f, 64.0f, 80.0f, |
| 593 | 24.0f, 40.0f, 64.0f, 80.0f, |
| 594 | 24.0f, 40.0f, 64.0f, 80.0f, |
| 595 | 24.0f, 40.0f, 64.0f, 80.0f, |
| 596 | |
| 597 | 36.0f, 60.0f, 96.0f, 120.0f, |
| 598 | 36.0f, 60.0f, 96.0f, 120.0f, |
| 599 | 36.0f, 60.0f, 96.0f, 120.0f, |
| 600 | 36.0f, 60.0f, 96.0f, 120.0f, |
| 601 | |
| 602 | 48.0f, 80.0f, 128.0f, 160.0f, |
| 603 | 48.0f, 80.0f, 128.0f, 160.0f, |
| 604 | 48.0f, 80.0f, 128.0f, 160.0f, |
| 605 | 48.0f, 80.0f, 128.0f, 160.0f, |
| 606 | }, |
| 607 | qScale, qOffset); |
| 608 | |
| 609 | auto outputExpected = QuantizedVector<T>( |
| 610 | { |
| 611 | 1.5f, 6.5f, 5.0f, |
| 612 | 3.0f, 13.0f, 10.0f, |
| 613 | 1.5f, 6.5f, 5.0f, |
| 614 | |
| 615 | 7.5f, 32.5f, 25.0f, |
| 616 | 15.0f, 65.0f, 50.0f, |
| 617 | 7.5f, 32.5f, 25.0f, |
| 618 | |
| 619 | 6.0f, 26.0f, 20.0f, |
| 620 | 12.0f, 52.0f, 40.0f, |
| 621 | 6.0f, 26.0f, 20.0f, |
| 622 | }, |
| 623 | qScale, qOffset); |
| 624 | |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 625 | if (dataLayout == armnn::DataLayout::NDHWC) |
| 626 | { |
| 627 | PermuteNCDHWToNDHWC(input, inputTensorInfo); |
| 628 | PermuteNCDHWToNDHWC(outputExpected, outputTensorInfo); |
| 629 | } |
| 630 | |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 631 | return SimplePooling3dTestImpl<ArmnnType>( |
| 632 | workloadFactory, memoryManager, tensorHandleFactory, descriptor, qScale, qOffset, |
| 633 | input, outputExpected, inputTensorInfo.GetShape(), outputTensorInfo.GetShape()); |
| 634 | } |
| 635 | |
| 636 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
| 637 | LayerTestResult<T, 5> SimpleL2Pooling3dTestCommon( |
| 638 | armnn::IWorkloadFactory& workloadFactory, |
| 639 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 640 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 641 | const armnn::DataLayout dataLayout, |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 642 | float qScale = 1.0f, |
| 643 | int32_t qOffset = 0) |
| 644 | { |
| 645 | armnn::Pooling3dDescriptor descriptor; |
| 646 | descriptor.m_PoolType = armnn::PoolingAlgorithm::L2; |
| 647 | descriptor.m_PoolWidth = descriptor.m_PoolHeight = descriptor.m_PoolDepth = 2; |
| 648 | descriptor.m_StrideX = descriptor.m_StrideY = descriptor.m_StrideZ = 2; |
| 649 | descriptor.m_PaddingMethod = armnn::PaddingMethod::Exclude; |
| 650 | descriptor.m_DataLayout = dataLayout; |
| 651 | |
| 652 | armnn::TensorInfo inputTensorInfo = armnnUtils::GetTensorInfo(1, 1, 4, 4, 4, dataLayout, ArmnnType); |
| 653 | armnn::TensorInfo outputTensorInfo = armnnUtils::GetTensorInfo(1, 1, 2, 2, 2, dataLayout, ArmnnType); |
| 654 | |
| 655 | // Set quantization parameters if the requested type is a quantized type. |
| 656 | if(armnn::IsQuantizedType<T>()) |
| 657 | { |
| 658 | inputTensorInfo.SetQuantizationScale(qScale); |
| 659 | inputTensorInfo.SetQuantizationOffset(qOffset); |
| 660 | outputTensorInfo.SetQuantizationScale(qScale); |
| 661 | outputTensorInfo.SetQuantizationOffset(qOffset); |
| 662 | } |
| 663 | |
| 664 | std::vector<T> inputData( |
| 665 | QuantizedVector<T>({ |
| 666 | 1.0f, 2.0f, 5.0f, 6.0f, |
| 667 | 3.0f, 4.0f, 7.0f, 8.0f, |
| 668 | 9.0f, 10.0f, 13.0f, 14.0f, |
| 669 | 11.0f, 12.0f, 15.0f, 16.0f, |
| 670 | |
| 671 | 17.0f, 18.0f, 21.0f, 22.0f, |
| 672 | 19.0f, 20.0f, 23.0f, 24.0f, |
| 673 | 25.0f, 26.0f, 29.0f, 30.0f, |
| 674 | 27.0f, 28.0f, 31.0f, 32.0f, |
| 675 | |
| 676 | 33.0f, 34.0f, 37.0f, 38.0f, |
| 677 | 35.0f, 36.0f, 39.0f, 40.0f, |
| 678 | 41.0f, 42.0f, 45.0f, 46.0f, |
| 679 | 43.0f, 44.0f, 47.0f, 48.0f, |
| 680 | |
| 681 | 49.0f, 50.0f, 53.0f, 54.0f, |
| 682 | 51.0f, 52.0f, 55.0f, 56.0f, |
| 683 | 57.0f, 58.0f, 61.0f, 62.0f, |
| 684 | 59.0f, 60.0f, 63.0f, 64.0f, |
| 685 | }, |
| 686 | qScale, qOffset)); |
| 687 | |
| 688 | std::vector<T> outputData( |
| 689 | QuantizedVector<T>({ |
| 690 | 13.2476412995f, 16.5981926727f, |
| 691 | 20.1866292382f, 23.9060661758f, |
| 692 | |
| 693 | 43.2608367926f, 47.1963981677f, |
| 694 | 51.1419592898f, 55.0953718564f, |
| 695 | }, |
| 696 | qScale, qOffset)); |
| 697 | |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 698 | if (dataLayout == armnn::DataLayout::NDHWC) |
| 699 | { |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 700 | PermuteNCDHWToNDHWC(inputData, inputTensorInfo); |
| 701 | PermuteNCDHWToNDHWC(outputData, outputTensorInfo); |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 702 | } |
| 703 | |
| 704 | return SimplePooling3dTestImpl<ArmnnType>( |
| 705 | workloadFactory, memoryManager, tensorHandleFactory, descriptor, qScale, qOffset, |
| 706 | inputData, outputData, inputTensorInfo.GetShape(), outputTensorInfo.GetShape()); |
| 707 | } |
| 708 | |
| 709 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
| 710 | LayerTestResult<T, 5> IgnorePaddingSimpleL2Pooling3dTestCommon( |
| 711 | armnn::IWorkloadFactory& workloadFactory, |
| 712 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 713 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 714 | const armnn::DataLayout dataLayout, |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 715 | float qScale = 1.0f, |
| 716 | int32_t qOffset = 0) |
| 717 | { |
| 718 | armnn::Pooling3dDescriptor descriptor; |
| 719 | descriptor.m_PoolType = armnn::PoolingAlgorithm::L2; |
| 720 | descriptor.m_PoolWidth = descriptor.m_PoolHeight = descriptor.m_PoolDepth = 2; |
| 721 | descriptor.m_StrideX = descriptor.m_StrideY = descriptor.m_StrideZ = 2; |
| 722 | descriptor.m_PadLeft = 1; |
| 723 | descriptor.m_PadRight = 1; |
| 724 | descriptor.m_PadTop = 1; |
| 725 | descriptor.m_PadBottom = 1; |
| 726 | descriptor.m_PadFront = 1; |
| 727 | descriptor.m_PadBack = 1; |
| 728 | descriptor.m_PaddingMethod = armnn::PaddingMethod::IgnoreValue; |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 729 | descriptor.m_DataLayout = dataLayout; |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 730 | |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 731 | armnn::TensorInfo inputTensorInfo = armnnUtils::GetTensorInfo( 1, 1, 4, 4, 4, dataLayout, ArmnnType); |
| 732 | armnn::TensorInfo outputTensorInfo = armnnUtils::GetTensorInfo( 1, 1, 3, 3, 3, dataLayout,ArmnnType); |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 733 | |
| 734 | // Set quantization parameters if the requested type is a quantized type. |
| 735 | if(armnn::IsQuantizedType<T>()) |
| 736 | { |
| 737 | inputTensorInfo.SetQuantizationScale(qScale); |
| 738 | inputTensorInfo.SetQuantizationOffset(qOffset); |
| 739 | outputTensorInfo.SetQuantizationScale(qScale); |
| 740 | outputTensorInfo.SetQuantizationOffset(qOffset); |
| 741 | } |
| 742 | |
| 743 | auto input = QuantizedVector<T>( |
| 744 | { |
| 745 | 1.0f, 2.0f, 3.0f, 4.0f, |
| 746 | 1.0f, 2.0f, 3.0f, 4.0f, |
| 747 | 1.0f, 2.0f, 3.0f, 4.0f, |
| 748 | 1.0f, 2.0f, 3.0f, 4.0f, |
| 749 | |
| 750 | 2.0f, 3.0f, 4.0f, 5.0f, |
| 751 | 2.0f, 3.0f, 4.0f, 5.0f, |
| 752 | 2.0f, 3.0f, 4.0f, 5.0f, |
| 753 | 2.0f, 3.0f, 4.0f, 5.0f, |
| 754 | |
| 755 | 3.0f, 4.0f, 5.0f, 6.0f, |
| 756 | 3.0f, 4.0f, 5.0f, 6.0f, |
| 757 | 3.0f, 4.0f, 5.0f, 6.0f, |
| 758 | 3.0f, 4.0f, 5.0f, 6.0f, |
| 759 | |
| 760 | 4.0f, 5.0f, 6.0f, 7.0f, |
| 761 | 4.0f, 5.0f, 6.0f, 7.0f, |
| 762 | 4.0f, 5.0f, 6.0f, 7.0f, |
| 763 | 4.0f, 5.0f, 6.0f, 7.0f, |
| 764 | }, |
| 765 | qScale, qOffset); |
| 766 | |
| 767 | float v111 = float(sqrt(pow(1,2)/8.0f)); |
| 768 | float v112 = float(sqrt((pow(2,2)+pow(3,2))/8.0f)); |
| 769 | float v113 = float(sqrt(pow(4,2)/8)); |
| 770 | |
| 771 | float v121 = float(sqrt((2*pow(1,2))/8.0f)); |
| 772 | float v122 = float(sqrt((2*pow(2,2)+2*pow(3,2))/8.0f)); |
| 773 | float v123 = float(sqrt((2*pow(4,2))/8.0f)); |
| 774 | |
| 775 | float v131 = v111; |
| 776 | float v132 = v112; |
| 777 | float v133 = v113; |
| 778 | |
| 779 | float v211 = float(sqrt((pow(2,2)+pow(3,2))/8.0f)); |
| 780 | float v212 = float(sqrt((pow(3,2)+2*pow(4,2)+pow(5,2))/8.0f)); |
| 781 | float v213 = float(sqrt((pow(5,2)+pow(6,2))/8.0f)); |
| 782 | |
| 783 | float v221 = float(sqrt((2*pow(2,2)+2*pow(3,2))/8.0f)); |
| 784 | float v222 = float(sqrt((2*pow(3,2)+4*pow(4,2)+2*pow(5,2))/8.0f)); |
| 785 | float v223 = float(sqrt((2*pow(5,2)+2*pow(6,2))/8.0f)); |
| 786 | |
| 787 | float v231 = v211; |
| 788 | float v232 = v212; |
| 789 | float v233 = v213; |
| 790 | |
| 791 | float v311 = float(sqrt(pow(4,2)/8.0f)); |
| 792 | float v312 = float(sqrt((pow(5,2)+pow(6,2))/8.0f)); |
| 793 | float v313 = float(sqrt(pow(7,2)/8)); |
| 794 | |
| 795 | float v321 = float(sqrt((2*pow(4,2))/8.0f)); |
| 796 | float v322 = float(sqrt((2*pow(5,2)+2*pow(6,2))/8.0f)); |
| 797 | float v323 = float(sqrt((2*pow(7,2))/8.0f)); |
| 798 | |
| 799 | float v331 = v311; |
| 800 | float v332 = v312; |
| 801 | float v333 = v313; |
| 802 | |
| 803 | auto outputExpected = QuantizedVector<T>( |
| 804 | { |
| 805 | v111, v112, v113, |
| 806 | v121, v122, v123, |
| 807 | v131, v132, v133, |
| 808 | |
| 809 | v211, v212, v213, |
| 810 | v221, v222, v223, |
| 811 | v231, v232, v233, |
| 812 | |
| 813 | v311, v312, v313, |
| 814 | v321, v322, v323, |
| 815 | v331, v332, v333, |
| 816 | }, |
| 817 | qScale, qOffset); |
| 818 | |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 819 | if (dataLayout == armnn::DataLayout::NDHWC) |
| 820 | { |
| 821 | PermuteNCDHWToNDHWC(input, inputTensorInfo); |
| 822 | PermuteNCDHWToNDHWC(outputExpected, outputTensorInfo); |
| 823 | } |
| 824 | |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 825 | return SimplePooling3dTestImpl<ArmnnType>( |
| 826 | workloadFactory, memoryManager, tensorHandleFactory, descriptor, qScale, qOffset, |
| 827 | input, outputExpected, inputTensorInfo.GetShape(), outputTensorInfo.GetShape()); |
| 828 | } |
| 829 | |
| 830 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 831 | LayerTestResult<T, 5> AsymmetricNonSquareMaxPooling3dWithPaddingOnlyPoolTestCommon( |
| 832 | armnn::IWorkloadFactory& workloadFactory, |
| 833 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 834 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
| 835 | const armnn::DataLayout dataLayout, |
| 836 | float qScale = 1.0f, |
| 837 | int32_t qOffset = 0) |
| 838 | { |
| 839 | armnn::TensorInfo inputTensorInfo = armnnUtils::GetTensorInfo( 1, 1, 1, 3, 1, dataLayout, ArmnnType); |
| 840 | armnn::TensorInfo outputTensorInfo = armnnUtils::GetTensorInfo( 1, 1, 2, 2, 1, dataLayout, ArmnnType); |
| 841 | |
| 842 | armnn::Pooling3dDescriptor descriptor; |
| 843 | descriptor.m_PoolType = armnn::PoolingAlgorithm::Max; |
| 844 | descriptor.m_PoolWidth = 1; |
| 845 | descriptor.m_PoolHeight = 2; |
| 846 | descriptor.m_PoolDepth = 3; |
| 847 | descriptor.m_StrideX = 1; |
| 848 | descriptor.m_StrideY = 2; |
| 849 | descriptor.m_StrideZ = 1; |
| 850 | descriptor.m_PadLeft = 0; |
| 851 | descriptor.m_PadRight = 0; |
| 852 | descriptor.m_PadTop = 2; |
| 853 | descriptor.m_PadBottom = 0; |
| 854 | descriptor.m_PadFront = 1; |
| 855 | descriptor.m_PadBack = 2; |
| 856 | descriptor.m_OutputShapeRounding = armnn::OutputShapeRounding::Floor; |
| 857 | descriptor.m_PaddingMethod = armnn::PaddingMethod::Exclude; |
| 858 | descriptor.m_DataLayout = dataLayout; |
| 859 | |
| 860 | // Construct input data. |
| 861 | auto input = QuantizedVector<T>( { 1.0f, 3.0f, 4.0f, }, qScale, qOffset); |
| 862 | |
| 863 | // These were calculated manually. |
| 864 | auto outputExpected = QuantizedVector<T>( { 0.0f, 3.0f, 0.0f, 3.0f, }, qScale, qOffset); |
| 865 | |
| 866 | if (dataLayout == armnn::DataLayout::NDHWC) |
| 867 | { |
| 868 | PermuteNCDHWToNDHWC<T>(input, inputTensorInfo); |
| 869 | PermuteNCDHWToNDHWC<T>(outputExpected, outputTensorInfo); |
| 870 | } |
| 871 | |
| 872 | return SimplePooling3dTestImpl<ArmnnType>( |
| 873 | workloadFactory, memoryManager, tensorHandleFactory, descriptor, qScale, qOffset, |
| 874 | input, outputExpected, inputTensorInfo.GetShape(), outputTensorInfo.GetShape()); |
| 875 | } |
| 876 | |
| 877 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 878 | LayerTestResult<T, 5> AsymmetricNonSquareMaxPooling3dTestCommon( |
| 879 | armnn::IWorkloadFactory& workloadFactory, |
| 880 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 881 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 882 | const armnn::DataLayout dataLayout, |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 883 | float qScale = 1.0f, |
| 884 | int32_t qOffset = 0) |
| 885 | { |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 886 | armnn::TensorInfo inputTensorInfo = armnnUtils::GetTensorInfo( 1, 1, 1, 3, 1, dataLayout, ArmnnType); |
| 887 | armnn::TensorInfo outputTensorInfo = armnnUtils::GetTensorInfo( 1, 1, 2, 2, 1, dataLayout, ArmnnType); |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 888 | |
| 889 | armnn::Pooling3dDescriptor descriptor; |
| 890 | descriptor.m_PoolType = armnn::PoolingAlgorithm::Max; |
| 891 | descriptor.m_PoolWidth = 1; |
| 892 | descriptor.m_PoolHeight = 2; |
| 893 | descriptor.m_PoolDepth = 3; |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 894 | descriptor.m_StrideX = 1; |
| 895 | descriptor.m_StrideY = 2; |
| 896 | descriptor.m_StrideZ = 1; |
| 897 | descriptor.m_PadLeft = 0; |
| 898 | descriptor.m_PadRight = 0; |
| 899 | descriptor.m_PadTop = 1; |
| 900 | descriptor.m_PadBottom = 0; |
| 901 | descriptor.m_PadFront = 1; |
| 902 | descriptor.m_PadBack = 2; |
| 903 | descriptor.m_OutputShapeRounding = armnn::OutputShapeRounding::Floor; |
| 904 | descriptor.m_PaddingMethod = armnn::PaddingMethod::Exclude; |
| 905 | descriptor.m_DataLayout = dataLayout; |
| 906 | |
| 907 | // Construct input data. |
| 908 | auto input = QuantizedVector<T>( { 1.0f, 3.0f, 4.0f, }, qScale, qOffset); |
| 909 | |
| 910 | // These were calculated manually. |
| 911 | auto outputExpected = QuantizedVector<T>( { 1.0f, 4.0f, 1.0f, 4.0f, }, qScale, qOffset); |
| 912 | |
| 913 | if (dataLayout == armnn::DataLayout::NDHWC) |
| 914 | { |
| 915 | PermuteNCDHWToNDHWC<T>(input, inputTensorInfo); |
| 916 | PermuteNCDHWToNDHWC<T>(outputExpected, outputTensorInfo); |
| 917 | } |
| 918 | |
| 919 | return SimplePooling3dTestImpl<ArmnnType>( |
| 920 | workloadFactory, memoryManager, tensorHandleFactory, descriptor, qScale, qOffset, |
| 921 | input, outputExpected, inputTensorInfo.GetShape(), outputTensorInfo.GetShape()); |
| 922 | } |
| 923 | |
| 924 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
| 925 | LayerTestResult<T, 5> AsymmetricNonSquareAveragePooling3dWithPaddingOnlyPoolTestCommon( |
| 926 | armnn::IWorkloadFactory& workloadFactory, |
| 927 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 928 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
| 929 | const armnn::DataLayout dataLayout, |
| 930 | float qScale = 1.0f, |
| 931 | int32_t qOffset = 0) |
| 932 | { |
| 933 | armnn::TensorInfo inputTensorInfo = armnnUtils::GetTensorInfo( 1, 1, 1, 3, 1, dataLayout, ArmnnType); |
| 934 | armnn::TensorInfo outputTensorInfo = armnnUtils::GetTensorInfo( 1, 1, 2, 2, 1, dataLayout, ArmnnType); |
| 935 | |
| 936 | armnn::Pooling3dDescriptor descriptor; |
| 937 | descriptor.m_PoolType = armnn::PoolingAlgorithm::Average; |
| 938 | descriptor.m_PoolWidth = 1; |
| 939 | descriptor.m_PoolHeight = 2; |
| 940 | descriptor.m_PoolDepth = 3; |
| 941 | descriptor.m_StrideX = 1; |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 942 | descriptor.m_StrideY = 2; |
| 943 | descriptor.m_StrideZ = 1; |
| 944 | descriptor.m_PadLeft = 0; |
| 945 | descriptor.m_PadRight = 0; |
| 946 | descriptor.m_PadTop = 2; |
| 947 | descriptor.m_PadBottom = 0; |
| 948 | descriptor.m_PadFront = 1; |
| 949 | descriptor.m_PadBack = 2; |
| 950 | descriptor.m_OutputShapeRounding = armnn::OutputShapeRounding::Floor; |
| 951 | descriptor.m_PaddingMethod = armnn::PaddingMethod::Exclude; |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 952 | descriptor.m_DataLayout = dataLayout; |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 953 | |
| 954 | // Construct input data. |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 955 | auto input = QuantizedVector<T>({ 1.0f, 3.0f, 4.0f, }, qScale, qOffset); |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 956 | |
| 957 | // These were calculated manually. |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 958 | auto outputExpected = QuantizedVector<T>( { 0.0f, 2.0f, 0.0f, 2.0f, }, qScale, qOffset); |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 959 | |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 960 | if (dataLayout == armnn::DataLayout::NDHWC) |
| 961 | { |
| 962 | PermuteNCDHWToNDHWC<T>(input, inputTensorInfo); |
| 963 | PermuteNCDHWToNDHWC<T>(outputExpected, outputTensorInfo); |
| 964 | } |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 965 | return SimplePooling3dTestImpl<ArmnnType>( |
| 966 | workloadFactory, memoryManager, tensorHandleFactory, descriptor, qScale, qOffset, |
| 967 | input, outputExpected, inputTensorInfo.GetShape(), outputTensorInfo.GetShape()); |
| 968 | } |
| 969 | |
| 970 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
| 971 | LayerTestResult<T, 5> AsymmetricNonSquareAveragePooling3dTestCommon( |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 972 | armnn::IWorkloadFactory& workloadFactory, |
| 973 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 974 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
| 975 | const armnn::DataLayout dataLayout, |
| 976 | float qScale = 1.0f, |
| 977 | int32_t qOffset = 0) |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 978 | { |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 979 | armnn::TensorInfo inputTensorInfo = armnnUtils::GetTensorInfo( 1, 1, 1, 3, 1, dataLayout, ArmnnType); |
| 980 | armnn::TensorInfo outputTensorInfo = armnnUtils::GetTensorInfo( 1, 1, 2, 2, 1, dataLayout, ArmnnType); |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 981 | |
| 982 | armnn::Pooling3dDescriptor descriptor; |
| 983 | descriptor.m_PoolType = armnn::PoolingAlgorithm::Average; |
| 984 | descriptor.m_PoolWidth = 1; |
| 985 | descriptor.m_PoolHeight = 2; |
| 986 | descriptor.m_PoolDepth = 3; |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 987 | descriptor.m_StrideX = 1; |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 988 | descriptor.m_StrideY = 2; |
| 989 | descriptor.m_StrideZ = 1; |
| 990 | descriptor.m_PadLeft = 0; |
| 991 | descriptor.m_PadRight = 0; |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 992 | descriptor.m_PadTop = 1; |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 993 | descriptor.m_PadBottom = 0; |
| 994 | descriptor.m_PadFront = 1; |
| 995 | descriptor.m_PadBack = 2; |
| 996 | descriptor.m_OutputShapeRounding = armnn::OutputShapeRounding::Floor; |
| 997 | descriptor.m_PaddingMethod = armnn::PaddingMethod::Exclude; |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 998 | descriptor.m_DataLayout = dataLayout; |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 999 | |
| 1000 | // Construct input data. |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 1001 | auto input = QuantizedVector<T>( { 1.0f, 3.0f, 4.0f, }, qScale, qOffset); |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 1002 | |
| 1003 | // These were calculated manually. |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 1004 | auto outputExpected = QuantizedVector<T>( { 1.0f, 3.5f, 1.0f, 3.5f, }, qScale, qOffset); |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 1005 | |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 1006 | if (dataLayout == armnn::DataLayout::NDHWC) |
| 1007 | { |
| 1008 | PermuteNCDHWToNDHWC<T>(input, inputTensorInfo); |
| 1009 | PermuteNCDHWToNDHWC<T>(outputExpected, outputTensorInfo); |
| 1010 | } |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 1011 | return SimplePooling3dTestImpl<ArmnnType>( |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 1012 | workloadFactory, memoryManager, tensorHandleFactory, descriptor, qScale, qOffset, |
| 1013 | input, outputExpected, inputTensorInfo.GetShape(), outputTensorInfo.GetShape()); |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 1014 | } |
| 1015 | |
| 1016 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 1017 | LayerTestResult<T, 5> AsymmetricNonSquareL2Pooling3dWithPaddingOnlyPoolTestCommon( |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 1018 | armnn::IWorkloadFactory& workloadFactory, |
| 1019 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 1020 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 1021 | const armnn::DataLayout dataLayout, |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 1022 | float qScale = 1.0f, |
| 1023 | int32_t qOffset = 0) |
| 1024 | { |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 1025 | armnn::TensorInfo inputTensorInfo = armnnUtils::GetTensorInfo( 1, 1, 1, 3, 1, dataLayout, ArmnnType); |
| 1026 | armnn::TensorInfo outputTensorInfo = armnnUtils::GetTensorInfo( 1, 1, 2, 2, 1, dataLayout, ArmnnType); |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 1027 | |
| 1028 | armnn::Pooling3dDescriptor descriptor; |
| 1029 | descriptor.m_PoolType = armnn::PoolingAlgorithm::L2; |
| 1030 | descriptor.m_PoolWidth = 1; |
| 1031 | descriptor.m_PoolHeight = 2; |
| 1032 | descriptor.m_PoolDepth = 3; |
| 1033 | descriptor.m_StrideX = 0; |
| 1034 | descriptor.m_StrideY = 2; |
| 1035 | descriptor.m_StrideZ = 1; |
| 1036 | descriptor.m_PadLeft = 0; |
| 1037 | descriptor.m_PadRight = 0; |
| 1038 | descriptor.m_PadTop = 2; |
| 1039 | descriptor.m_PadBottom = 0; |
| 1040 | descriptor.m_PadFront = 1; |
| 1041 | descriptor.m_PadBack = 2; |
| 1042 | descriptor.m_OutputShapeRounding = armnn::OutputShapeRounding::Floor; |
| 1043 | descriptor.m_PaddingMethod = armnn::PaddingMethod::Exclude; |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 1044 | descriptor.m_DataLayout = dataLayout; |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 1045 | |
| 1046 | // Construct input data. |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 1047 | auto input = QuantizedVector<T>( { 1.0f, 3.0f, 4.0f, }, qScale, qOffset); |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 1048 | |
| 1049 | // These were calculated manually. |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 1050 | auto outputExpected = QuantizedVector<T>( { 0.0f, 2.2360679775f, 0.0f, 2.2360679775f, }, qScale, qOffset); |
| 1051 | |
| 1052 | if (dataLayout == armnn::DataLayout::NDHWC) |
| 1053 | { |
| 1054 | PermuteNCDHWToNDHWC<T>(input, inputTensorInfo); |
| 1055 | PermuteNCDHWToNDHWC<T>(outputExpected, outputTensorInfo); |
| 1056 | } |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 1057 | |
| 1058 | return SimplePooling3dTestImpl<ArmnnType>( |
| 1059 | workloadFactory, memoryManager, tensorHandleFactory, descriptor, qScale, qOffset, |
| 1060 | input, outputExpected, inputTensorInfo.GetShape(), outputTensorInfo.GetShape()); |
| 1061 | } |
| 1062 | |
| 1063 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 1064 | LayerTestResult<T, 5> AsymmetricNonSquareL2Pooling3dTestCommon( |
| 1065 | armnn::IWorkloadFactory& workloadFactory, |
| 1066 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 1067 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
| 1068 | const armnn::DataLayout dataLayout, |
| 1069 | float qScale = 1.0f, |
| 1070 | int32_t qOffset = 0) |
| 1071 | { |
| 1072 | armnn::TensorInfo inputTensorInfo = armnnUtils::GetTensorInfo( 1, 1, 1, 3, 1, dataLayout, ArmnnType); |
| 1073 | armnn::TensorInfo outputTensorInfo = armnnUtils::GetTensorInfo( 1, 1, 2, 2, 1, dataLayout, ArmnnType); |
| 1074 | |
| 1075 | armnn::Pooling3dDescriptor descriptor; |
| 1076 | descriptor.m_PoolType = armnn::PoolingAlgorithm::L2; |
| 1077 | descriptor.m_PoolWidth = 1; |
| 1078 | descriptor.m_PoolHeight = 2; |
| 1079 | descriptor.m_PoolDepth = 3; |
| 1080 | descriptor.m_StrideX = 1; |
| 1081 | descriptor.m_StrideY = 2; |
| 1082 | descriptor.m_StrideZ = 1; |
| 1083 | descriptor.m_PadLeft = 0; |
| 1084 | descriptor.m_PadRight = 0; |
| 1085 | descriptor.m_PadTop = 1; |
| 1086 | descriptor.m_PadBottom = 0; |
| 1087 | descriptor.m_PadFront = 1; |
| 1088 | descriptor.m_PadBack = 2; |
| 1089 | descriptor.m_OutputShapeRounding = armnn::OutputShapeRounding::Floor; |
| 1090 | descriptor.m_PaddingMethod = armnn::PaddingMethod::Exclude; |
| 1091 | descriptor.m_DataLayout = dataLayout; |
| 1092 | |
| 1093 | // Construct input data. |
| 1094 | auto input = QuantizedVector<T>( { 1.0f, 3.0f, 4.0f, }, qScale, qOffset); |
| 1095 | |
| 1096 | // These were calculated manually. |
| 1097 | auto outputExpected = QuantizedVector<T>( { 1.0f, 3.53553390593f, 1.0f, 3.53553390593f, }, qScale, qOffset); |
| 1098 | |
| 1099 | if (dataLayout == armnn::DataLayout::NDHWC) |
| 1100 | { |
| 1101 | PermuteNCDHWToNDHWC<T>(input, inputTensorInfo); |
| 1102 | PermuteNCDHWToNDHWC<T>(outputExpected, outputTensorInfo); |
| 1103 | } |
| 1104 | |
| 1105 | return SimplePooling3dTestImpl<ArmnnType>( |
| 1106 | workloadFactory, memoryManager, tensorHandleFactory, descriptor, qScale, qOffset, |
| 1107 | input, outputExpected, inputTensorInfo.GetShape(), outputTensorInfo.GetShape()); |
| 1108 | } |
| 1109 | |
| 1110 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 1111 | LayerTestResult<T, 5> ComparePooling3dTestCommon( |
| 1112 | armnn::IWorkloadFactory& workloadFactory, |
| 1113 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 1114 | armnn::IWorkloadFactory& refWorkloadFactory, |
| 1115 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
| 1116 | const armnn::ITensorHandleFactory& refTensorHandleFactory, |
| 1117 | armnn::PoolingAlgorithm poolingType, |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 1118 | const armnn::DataLayout dataLayout, |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 1119 | float qScale = 1.0f, |
| 1120 | int32_t qOffset = 0) |
| 1121 | { |
| 1122 | IgnoreUnused(memoryManager); |
| 1123 | const unsigned int inputWidth = 16; |
| 1124 | const unsigned int inputHeight = 32; |
| 1125 | const unsigned int inputDepth = 48; |
| 1126 | const unsigned int channelCount = 2; |
| 1127 | const unsigned int batchSize = 5; |
| 1128 | |
| 1129 | const unsigned int poolSize = 3; |
| 1130 | const unsigned int strideX = 2; |
| 1131 | const unsigned int strideY = 4; |
| 1132 | const unsigned int strideZ = 6; |
| 1133 | const unsigned int padX = 0; |
| 1134 | const unsigned int padY = 0; |
| 1135 | const unsigned int padZ = 0; |
| 1136 | |
| 1137 | const unsigned int outputWidth = (inputWidth + 2 * padX + strideX - poolSize) / strideX; |
| 1138 | const unsigned int outputHeight = (inputHeight + 2 * padY + strideY - poolSize) / strideY; |
| 1139 | const unsigned int outputDepth = (inputDepth + 2 * padZ + strideZ - poolSize) / strideZ; |
| 1140 | |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 1141 | armnn::TensorInfo inputTensorInfo = armnnUtils::GetTensorInfo(batchSize, channelCount, inputDepth, inputHeight, |
| 1142 | inputWidth, dataLayout, ArmnnType); |
| 1143 | armnn::TensorInfo outputTensorInfo = armnnUtils::GetTensorInfo(batchSize, channelCount, outputDepth, outputHeight, |
| 1144 | outputWidth, dataLayout, ArmnnType); |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 1145 | |
| 1146 | // Set quantization parameters if the requested type is a quantized type. |
| 1147 | if(armnn::IsQuantizedType<T>()) |
| 1148 | { |
| 1149 | inputTensorInfo.SetQuantizationScale(qScale); |
| 1150 | inputTensorInfo.SetQuantizationOffset(qOffset); |
| 1151 | outputTensorInfo.SetQuantizationScale(qScale); |
| 1152 | outputTensorInfo.SetQuantizationOffset(qOffset); |
| 1153 | } |
| 1154 | |
| 1155 | std::vector<T> input = MakeRandomTensor<T>(inputTensorInfo, 81715); |
| 1156 | std::vector<T> actualOutput(outputTensorInfo.GetNumElements()); |
| 1157 | std::vector<T> expectedOutput(outputTensorInfo.GetNumElements()); |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 1158 | LayerTestResult<T, 5> comparisonResult(outputTensorInfo); |
| 1159 | |
| 1160 | std::unique_ptr<armnn::ITensorHandle> inputHandle = tensorHandleFactory.CreateTensorHandle(inputTensorInfo); |
| 1161 | std::unique_ptr<armnn::ITensorHandle> outputHandle = tensorHandleFactory.CreateTensorHandle(outputTensorInfo); |
| 1162 | |
| 1163 | armnn::Pooling3dQueueDescriptor data; |
| 1164 | armnn::WorkloadInfo info; |
| 1165 | AddInputToWorkload(data, info, inputTensorInfo, inputHandle.get()); |
| 1166 | AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get()); |
| 1167 | data.m_Parameters.m_PoolType = poolingType; |
| 1168 | data.m_Parameters.m_PoolWidth = poolSize; |
| 1169 | data.m_Parameters.m_PoolHeight = poolSize; |
| 1170 | data.m_Parameters.m_PoolDepth = poolSize; |
| 1171 | data.m_Parameters.m_StrideX = strideX; |
| 1172 | data.m_Parameters.m_StrideY = strideY; |
| 1173 | data.m_Parameters.m_StrideZ = strideZ; |
| 1174 | data.m_Parameters.m_PadLeft = padX; |
| 1175 | data.m_Parameters.m_PadRight = padX; |
| 1176 | data.m_Parameters.m_PadTop = padY; |
| 1177 | data.m_Parameters.m_PadBottom = padY; |
| 1178 | data.m_Parameters.m_PadFront = padZ; |
| 1179 | data.m_Parameters.m_PadBack = padZ; |
| 1180 | data.m_Parameters.m_OutputShapeRounding = armnn::OutputShapeRounding::Floor; |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 1181 | data.m_Parameters.m_DataLayout = dataLayout; |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 1182 | |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 1183 | std::unique_ptr<armnn::ITensorHandle> outputHandleRef = |
| 1184 | refTensorHandleFactory.CreateTensorHandle(outputTensorInfo); |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 1185 | std::unique_ptr<armnn::ITensorHandle> inputHandleRef = refTensorHandleFactory.CreateTensorHandle(inputTensorInfo); |
| 1186 | |
| 1187 | // Don't execute if Pooling is not supported, as an exception will be raised. |
| 1188 | armnn::BackendId backend = workloadFactory.GetBackendId(); |
| 1189 | std::string reasonIfUnsupported; |
| 1190 | armnn::LayerSupportHandle handle = armnn::GetILayerSupportByBackendId(backend); |
| 1191 | comparisonResult.m_Supported = handle.IsPooling3dSupported(inputTensorInfo, |
| 1192 | outputTensorInfo, |
| 1193 | data.m_Parameters, |
| 1194 | reasonIfUnsupported); |
| 1195 | if (!comparisonResult.m_Supported) |
| 1196 | { |
| 1197 | return comparisonResult; |
| 1198 | } |
| 1199 | |
| 1200 | armnn::Pooling3dQueueDescriptor refData = data; |
| 1201 | armnn::WorkloadInfo refInfo = info; |
| 1202 | SetWorkloadInput(refData, refInfo, 0, inputTensorInfo, inputHandleRef.get()); |
| 1203 | SetWorkloadOutput(refData, refInfo, 0, outputTensorInfo, outputHandleRef.get()); |
| 1204 | |
Teresa Charlin | 611c7fb | 2022-01-07 09:47:29 +0000 | [diff] [blame] | 1205 | std::unique_ptr<armnn::IWorkload> workload |
| 1206 | = workloadFactory.CreateWorkload(armnn::LayerType::Pooling3d, data, info); |
| 1207 | std::unique_ptr<armnn::IWorkload> workloadRef |
| 1208 | = refWorkloadFactory.CreateWorkload(armnn::LayerType::Pooling3d, refData, refInfo); |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 1209 | |
| 1210 | outputHandleRef->Allocate(); |
| 1211 | inputHandleRef->Allocate(); |
| 1212 | inputHandle->Allocate(); |
| 1213 | outputHandle->Allocate(); |
| 1214 | |
| 1215 | CopyDataToITensorHandle(inputHandle.get(), input.data()); |
| 1216 | CopyDataToITensorHandle(inputHandleRef.get(), input.data()); |
| 1217 | |
| 1218 | workload->Execute(); |
| 1219 | workloadRef->Execute(); |
| 1220 | |
| 1221 | CopyDataFromITensorHandle(actualOutput.data(), outputHandle.get()); |
| 1222 | CopyDataFromITensorHandle(expectedOutput.data(), outputHandleRef.get()); |
| 1223 | |
| 1224 | comparisonResult.m_ActualData = actualOutput; |
| 1225 | comparisonResult.m_ExpectedData = expectedOutput; |
| 1226 | |
| 1227 | return comparisonResult; |
| 1228 | } |
| 1229 | |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 1230 | } // anonymous namespace |
| 1231 | |
| 1232 | LayerTestResult<float, 5> SimpleMaxPooling3dSize2x2x2Stride1x1x1Test( |
| 1233 | armnn::IWorkloadFactory& workloadFactory, |
| 1234 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 1235 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
| 1236 | const armnn::DataLayout dataLayout) |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 1237 | { |
| 1238 | return SimpleMaxPooling3dSize2x2x2Stride1x1x1TestCommon<armnn::DataType::Float32>( |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 1239 | workloadFactory, memoryManager, tensorHandleFactory, dataLayout); |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 1240 | } |
| 1241 | |
| 1242 | LayerTestResult<uint8_t, 5> SimpleMaxPooling3dSize2x2x2Stride1x1x1Uint8Test( |
| 1243 | armnn::IWorkloadFactory& workloadFactory, |
| 1244 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 1245 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
| 1246 | const armnn::DataLayout dataLayout) |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 1247 | { |
| 1248 | return SimpleMaxPooling3dSize2x2x2Stride1x1x1TestCommon<armnn::DataType::QAsymmU8>( |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 1249 | workloadFactory, memoryManager, tensorHandleFactory, dataLayout, 0.1f, 128); |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 1250 | } |
| 1251 | |
| 1252 | LayerTestResult<int16_t, 5> SimpleMaxPooling3dSize2x2x2Stride1x1x1Int16Test( |
| 1253 | armnn::IWorkloadFactory& workloadFactory, |
| 1254 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 1255 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
| 1256 | const armnn::DataLayout dataLayout) |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 1257 | { |
| 1258 | return SimpleMaxPooling3dSize2x2x2Stride1x1x1TestCommon<armnn::DataType::QSymmS16>( |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 1259 | workloadFactory, memoryManager, tensorHandleFactory, dataLayout); |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 1260 | } |
| 1261 | |
| 1262 | LayerTestResult<float, 5> SimpleMaxPooling3dTest( |
| 1263 | armnn::IWorkloadFactory& workloadFactory, |
| 1264 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 1265 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
| 1266 | const armnn::DataLayout dataLayout) |
| 1267 | { |
| 1268 | return SimpleMaxPooling3dTestCommon<armnn::DataType::Float32>( |
| 1269 | workloadFactory, memoryManager, tensorHandleFactory, dataLayout); |
| 1270 | } |
| 1271 | |
| 1272 | LayerTestResult<uint8_t, 5> SimpleMaxPooling3dUint8Test( |
| 1273 | armnn::IWorkloadFactory& workloadFactory, |
| 1274 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 1275 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
| 1276 | const armnn::DataLayout dataLayout) |
| 1277 | { |
| 1278 | return SimpleMaxPooling3dTestCommon<armnn::DataType::QAsymmU8>( |
| 1279 | workloadFactory, memoryManager, tensorHandleFactory, dataLayout); |
| 1280 | } |
| 1281 | |
| 1282 | LayerTestResult<int16_t, 5> SimpleMaxPooling3dInt16Test( |
| 1283 | armnn::IWorkloadFactory& workloadFactory, |
| 1284 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 1285 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
| 1286 | const armnn::DataLayout dataLayout) |
| 1287 | { |
| 1288 | return SimpleMaxPooling3dTestCommon<armnn::DataType::QSymmS16>( |
| 1289 | workloadFactory, memoryManager, tensorHandleFactory, dataLayout); |
| 1290 | } |
| 1291 | |
| 1292 | LayerTestResult<float, 5> IgnorePaddingSimpleMaxPooling3dTest( |
| 1293 | armnn::IWorkloadFactory& workloadFactory, |
| 1294 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 1295 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
| 1296 | const armnn::DataLayout dataLayout) |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 1297 | { |
| 1298 | return IgnorePaddingSimpleMaxPooling3dTestCommon<armnn::DataType::Float32>( |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 1299 | workloadFactory, memoryManager, tensorHandleFactory, dataLayout); |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 1300 | } |
| 1301 | |
| 1302 | LayerTestResult<uint8_t, 5> IgnorePaddingSimpleMaxPooling3dUint8Test( |
| 1303 | armnn::IWorkloadFactory& workloadFactory, |
| 1304 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 1305 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
| 1306 | const armnn::DataLayout dataLayout) |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 1307 | { |
| 1308 | return IgnorePaddingSimpleMaxPooling3dTestCommon<armnn::DataType::QAsymmU8>( |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 1309 | workloadFactory, memoryManager, tensorHandleFactory,dataLayout, 1.0f, -5); |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 1310 | } |
| 1311 | |
| 1312 | LayerTestResult<int16_t, 5> IgnorePaddingSimpleMaxPooling3dInt16Test( |
| 1313 | armnn::IWorkloadFactory& workloadFactory, |
| 1314 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 1315 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
| 1316 | const armnn::DataLayout dataLayout) |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 1317 | { |
| 1318 | return IgnorePaddingSimpleMaxPooling3dTestCommon<armnn::DataType::QSymmS16>( |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 1319 | workloadFactory, memoryManager, tensorHandleFactory, dataLayout); |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 1320 | } |
| 1321 | |
| 1322 | LayerTestResult<float, 5> SimpleAveragePooling3dTest( |
| 1323 | armnn::IWorkloadFactory& workloadFactory, |
| 1324 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 1325 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
| 1326 | const armnn::DataLayout dataLayout) |
| 1327 | { |
| 1328 | return SimpleAveragePooling3dTestCommon<armnn::DataType::Float32>( |
| 1329 | workloadFactory, memoryManager, tensorHandleFactory, dataLayout); |
| 1330 | } |
| 1331 | |
| 1332 | LayerTestResult<uint8_t, 5> SimpleAveragePooling3dUint8Test( |
| 1333 | armnn::IWorkloadFactory& workloadFactory, |
| 1334 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 1335 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
| 1336 | const armnn::DataLayout dataLayout) |
| 1337 | { |
| 1338 | return SimpleAveragePooling3dTestCommon<armnn::DataType::QAsymmU8>( |
| 1339 | workloadFactory, memoryManager, tensorHandleFactory, dataLayout); |
| 1340 | } |
| 1341 | |
| 1342 | LayerTestResult<int16_t, 5> SimpleAveragePooling3dInt16Test( |
| 1343 | armnn::IWorkloadFactory& workloadFactory, |
| 1344 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 1345 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
| 1346 | const armnn::DataLayout dataLayout) |
| 1347 | { |
| 1348 | return SimpleAveragePooling3dTestCommon<armnn::DataType::QSymmS16>( |
| 1349 | workloadFactory, memoryManager, tensorHandleFactory, dataLayout); |
| 1350 | } |
| 1351 | |
| 1352 | LayerTestResult<float, 5> SimpleL2Pooling3dTest( |
| 1353 | armnn::IWorkloadFactory& workloadFactory, |
| 1354 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 1355 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
| 1356 | const armnn::DataLayout dataLayout) |
| 1357 | { |
| 1358 | return SimpleL2Pooling3dTestCommon<armnn::DataType::Float32>( |
| 1359 | workloadFactory, memoryManager, tensorHandleFactory, dataLayout); |
| 1360 | } |
| 1361 | |
| 1362 | LayerTestResult<uint8_t, 5> SimpleL2Pooling3dUint8Test( |
| 1363 | armnn::IWorkloadFactory& workloadFactory, |
| 1364 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 1365 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
| 1366 | const armnn::DataLayout dataLayout) |
| 1367 | { |
| 1368 | return SimpleL2Pooling3dTestCommon<armnn::DataType::QAsymmU8>( |
| 1369 | workloadFactory, memoryManager, tensorHandleFactory, dataLayout); |
| 1370 | } |
| 1371 | |
| 1372 | LayerTestResult<int16_t, 5> SimpleL2Pooling3dInt16Test( |
| 1373 | armnn::IWorkloadFactory& workloadFactory, |
| 1374 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 1375 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
| 1376 | const armnn::DataLayout dataLayout) |
| 1377 | { |
| 1378 | return SimpleL2Pooling3dTestCommon<armnn::DataType::QSymmS16>( |
| 1379 | workloadFactory, memoryManager, tensorHandleFactory, dataLayout); |
| 1380 | } |
| 1381 | |
| 1382 | LayerTestResult<float, 5> LargeTensorsAveragePooling3dTest( |
| 1383 | armnn::IWorkloadFactory& workloadFactory, |
| 1384 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 1385 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
| 1386 | const armnn::DataLayout dataLayout) |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 1387 | { |
| 1388 | return LargeTensorsAveragePooling3dTestCommon<armnn::DataType::Float32>( |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 1389 | workloadFactory, memoryManager, tensorHandleFactory, dataLayout); |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 1390 | } |
| 1391 | |
| 1392 | LayerTestResult<uint8_t, 5> LargeTensorsAveragePooling3dUint8Test( |
| 1393 | armnn::IWorkloadFactory& workloadFactory, |
| 1394 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 1395 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
| 1396 | const armnn::DataLayout dataLayout) |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 1397 | { |
| 1398 | return LargeTensorsAveragePooling3dTestCommon<armnn::DataType::QAsymmU8>( |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 1399 | workloadFactory, memoryManager, tensorHandleFactory, dataLayout, 0.5, -1); |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 1400 | } |
| 1401 | |
| 1402 | LayerTestResult<int16_t, 5> LargeTensorsAveragePooling3dInt16Test( |
| 1403 | armnn::IWorkloadFactory& workloadFactory, |
| 1404 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 1405 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
| 1406 | const armnn::DataLayout dataLayout) |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 1407 | { |
| 1408 | return LargeTensorsAveragePooling3dTestCommon<armnn::DataType::QSymmS16>( |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 1409 | workloadFactory, memoryManager, tensorHandleFactory, dataLayout); |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 1410 | } |
| 1411 | |
| 1412 | LayerTestResult<float, 5> IgnorePaddingSimpleAveragePooling3dTest( |
| 1413 | armnn::IWorkloadFactory& workloadFactory, |
| 1414 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 1415 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
| 1416 | const armnn::DataLayout dataLayout) |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 1417 | { |
| 1418 | return IgnorePaddingSimpleAveragePooling3dTestCommon<armnn::DataType::Float32>( |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 1419 | workloadFactory, memoryManager, tensorHandleFactory, dataLayout); |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 1420 | } |
| 1421 | |
| 1422 | LayerTestResult<uint8_t, 5> IgnorePaddingSimpleAveragePooling3dUint8Test( |
| 1423 | armnn::IWorkloadFactory& workloadFactory, |
| 1424 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 1425 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
| 1426 | const armnn::DataLayout dataLayout) |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 1427 | { |
| 1428 | return IgnorePaddingSimpleAveragePooling3dTestCommon<armnn::DataType::QAsymmU8>( |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 1429 | workloadFactory, memoryManager, tensorHandleFactory, dataLayout, 1.0f, -5); |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 1430 | } |
| 1431 | |
| 1432 | LayerTestResult<int16_t, 5> IgnorePaddingSimpleAveragePooling3dInt16Test( |
| 1433 | armnn::IWorkloadFactory& workloadFactory, |
| 1434 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 1435 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
| 1436 | const armnn::DataLayout dataLayout) |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 1437 | { |
| 1438 | return IgnorePaddingSimpleAveragePooling3dTestCommon<armnn::DataType::QSymmS16>( |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 1439 | workloadFactory, memoryManager, tensorHandleFactory, dataLayout); |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 1440 | } |
| 1441 | |
| 1442 | LayerTestResult<float, 5> IgnorePaddingSimpleL2Pooling3dTest( |
| 1443 | armnn::IWorkloadFactory& workloadFactory, |
| 1444 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 1445 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
| 1446 | const armnn::DataLayout dataLayout) |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 1447 | { |
| 1448 | return IgnorePaddingSimpleL2Pooling3dTestCommon<armnn::DataType::Float32>( |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 1449 | workloadFactory, memoryManager, tensorHandleFactory, dataLayout); |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 1450 | } |
| 1451 | |
| 1452 | LayerTestResult<uint8_t, 5> IgnorePaddingSimpleL2Pooling3dUint8Test( |
| 1453 | armnn::IWorkloadFactory& workloadFactory, |
| 1454 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 1455 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
| 1456 | const armnn::DataLayout dataLayout) |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 1457 | { |
| 1458 | return IgnorePaddingSimpleL2Pooling3dTestCommon<armnn::DataType::QAsymmU8>( |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 1459 | workloadFactory, memoryManager, tensorHandleFactory, dataLayout, 1.0f, -5); |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 1460 | } |
| 1461 | |
| 1462 | LayerTestResult<int16_t, 5> IgnorePaddingSimpleL2Pooling3dInt16Test( |
| 1463 | armnn::IWorkloadFactory& workloadFactory, |
| 1464 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 1465 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
| 1466 | const armnn::DataLayout dataLayout) |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 1467 | { |
| 1468 | return IgnorePaddingSimpleL2Pooling3dTestCommon<armnn::DataType::QSymmS16>( |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 1469 | workloadFactory, memoryManager, tensorHandleFactory, dataLayout); |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 1470 | } |
| 1471 | |
| 1472 | LayerTestResult<float, 5> AsymmetricNonSquareMaxPooling3dTest( |
| 1473 | armnn::IWorkloadFactory& workloadFactory, |
| 1474 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 1475 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
| 1476 | const armnn::DataLayout dataLayout) |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 1477 | { |
| 1478 | return AsymmetricNonSquareMaxPooling3dTestCommon<armnn::DataType::Float32>( |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 1479 | workloadFactory, memoryManager, tensorHandleFactory, dataLayout); |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 1480 | } |
| 1481 | |
| 1482 | LayerTestResult<uint8_t, 5> AsymmetricNonSquareMaxPooling3dUint8Test( |
| 1483 | armnn::IWorkloadFactory& workloadFactory, |
| 1484 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 1485 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
| 1486 | const armnn::DataLayout dataLayout) |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 1487 | { |
| 1488 | return AsymmetricNonSquareMaxPooling3dTestCommon<armnn::DataType::QAsymmU8>( |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 1489 | workloadFactory, memoryManager, tensorHandleFactory, dataLayout); |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 1490 | } |
| 1491 | |
| 1492 | LayerTestResult<int16_t, 5> AsymmetricNonSquareMaxPooling3dInt16Test( |
| 1493 | armnn::IWorkloadFactory& workloadFactory, |
| 1494 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 1495 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
| 1496 | const armnn::DataLayout dataLayout) |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 1497 | { |
| 1498 | return AsymmetricNonSquareMaxPooling3dTestCommon<armnn::DataType::QSymmS16>( |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 1499 | workloadFactory, memoryManager, tensorHandleFactory, dataLayout); |
| 1500 | } |
| 1501 | |
| 1502 | LayerTestResult<float, 5> AsymmetricNonSquareMaxPooling3dWithPaddingOnlyPoolTest( |
| 1503 | armnn::IWorkloadFactory& workloadFactory, |
| 1504 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 1505 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
| 1506 | const armnn::DataLayout dataLayout) |
| 1507 | { |
| 1508 | return AsymmetricNonSquareMaxPooling3dWithPaddingOnlyPoolTestCommon<armnn::DataType::Float32>( |
| 1509 | workloadFactory, memoryManager, tensorHandleFactory, dataLayout); |
| 1510 | } |
| 1511 | |
| 1512 | LayerTestResult<uint8_t, 5> AsymmetricNonSquareMaxPooling3dWithPaddingOnlyPoolUint8Test( |
| 1513 | armnn::IWorkloadFactory& workloadFactory, |
| 1514 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 1515 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
| 1516 | const armnn::DataLayout dataLayout) |
| 1517 | { |
| 1518 | return AsymmetricNonSquareMaxPooling3dWithPaddingOnlyPoolTestCommon<armnn::DataType::QAsymmU8>( |
| 1519 | workloadFactory, memoryManager, tensorHandleFactory, dataLayout); |
| 1520 | } |
| 1521 | |
| 1522 | LayerTestResult<int16_t, 5> AsymmetricNonSquareMaxPooling3dWithPaddingOnlyPoolInt16Test( |
| 1523 | armnn::IWorkloadFactory& workloadFactory, |
| 1524 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 1525 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
| 1526 | const armnn::DataLayout dataLayout) |
| 1527 | { |
| 1528 | return AsymmetricNonSquareMaxPooling3dWithPaddingOnlyPoolTestCommon<armnn::DataType::QSymmS16>( |
| 1529 | workloadFactory, memoryManager, tensorHandleFactory, dataLayout); |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 1530 | } |
| 1531 | |
| 1532 | LayerTestResult<float, 5> AsymmetricNonSquareAveragePooling3dTest( |
| 1533 | armnn::IWorkloadFactory& workloadFactory, |
| 1534 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 1535 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
| 1536 | const armnn::DataLayout dataLayout) |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 1537 | { |
| 1538 | return AsymmetricNonSquareAveragePooling3dTestCommon<armnn::DataType::Float32>( |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 1539 | workloadFactory, memoryManager, tensorHandleFactory, dataLayout); |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 1540 | } |
| 1541 | |
| 1542 | LayerTestResult<uint8_t, 5> AsymmetricNonSquareAveragePooling3dUint8Test( |
| 1543 | armnn::IWorkloadFactory& workloadFactory, |
| 1544 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 1545 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
| 1546 | const armnn::DataLayout dataLayout) |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 1547 | { |
| 1548 | return AsymmetricNonSquareAveragePooling3dTestCommon<armnn::DataType::QAsymmU8>( |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 1549 | workloadFactory, memoryManager, tensorHandleFactory, dataLayout); |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 1550 | } |
| 1551 | |
| 1552 | LayerTestResult<int16_t, 5> AsymmetricNonSquareAveragePooling3dInt16Test( |
| 1553 | armnn::IWorkloadFactory& workloadFactory, |
| 1554 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 1555 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
| 1556 | const armnn::DataLayout dataLayout) |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 1557 | { |
| 1558 | return AsymmetricNonSquareAveragePooling3dTestCommon<armnn::DataType::QSymmS16>( |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 1559 | workloadFactory, memoryManager, tensorHandleFactory, dataLayout); |
| 1560 | } |
| 1561 | |
| 1562 | LayerTestResult<float, 5> AsymmetricNonSquareAveragePooling3dWithPaddingOnlyPoolTest( |
| 1563 | armnn::IWorkloadFactory& workloadFactory, |
| 1564 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 1565 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
| 1566 | const armnn::DataLayout dataLayout) |
| 1567 | { |
| 1568 | return AsymmetricNonSquareAveragePooling3dWithPaddingOnlyPoolTestCommon<armnn::DataType::Float32>( |
| 1569 | workloadFactory, memoryManager, tensorHandleFactory, dataLayout); |
| 1570 | } |
| 1571 | |
| 1572 | LayerTestResult<uint8_t, 5> AsymmetricNonSquareAveragePooling3dWithPaddingOnlyPoolUint8Test( |
| 1573 | armnn::IWorkloadFactory& workloadFactory, |
| 1574 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 1575 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
| 1576 | const armnn::DataLayout dataLayout) |
| 1577 | { |
| 1578 | return AsymmetricNonSquareAveragePooling3dWithPaddingOnlyPoolTestCommon<armnn::DataType::QAsymmU8>( |
| 1579 | workloadFactory, memoryManager, tensorHandleFactory, dataLayout); |
| 1580 | } |
| 1581 | |
| 1582 | LayerTestResult<int16_t, 5> AsymmetricNonSquareAveragePooling3dWithPaddingOnlyPoolInt16Test( |
| 1583 | armnn::IWorkloadFactory& workloadFactory, |
| 1584 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 1585 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
| 1586 | const armnn::DataLayout dataLayout) |
| 1587 | { |
| 1588 | return AsymmetricNonSquareAveragePooling3dWithPaddingOnlyPoolTestCommon<armnn::DataType::QSymmS16>( |
| 1589 | workloadFactory, memoryManager, tensorHandleFactory, dataLayout); |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 1590 | } |
| 1591 | |
| 1592 | LayerTestResult<float, 5> AsymmetricNonSquareL2Pooling3dTest( |
| 1593 | armnn::IWorkloadFactory& workloadFactory, |
| 1594 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 1595 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
| 1596 | const armnn::DataLayout dataLayout) |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 1597 | { |
| 1598 | return AsymmetricNonSquareL2Pooling3dTestCommon<armnn::DataType::Float32>( |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 1599 | workloadFactory, memoryManager, tensorHandleFactory, dataLayout); |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 1600 | } |
| 1601 | |
| 1602 | LayerTestResult<uint8_t, 5> AsymmetricNonSquareL2Pooling3dUint8Test( |
| 1603 | armnn::IWorkloadFactory& workloadFactory, |
| 1604 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 1605 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
| 1606 | const armnn::DataLayout dataLayout) |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 1607 | { |
| 1608 | return AsymmetricNonSquareL2Pooling3dTestCommon<armnn::DataType::QAsymmU8>( |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 1609 | workloadFactory, memoryManager, tensorHandleFactory, dataLayout); |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 1610 | } |
| 1611 | |
| 1612 | LayerTestResult<int16_t, 5> AsymmetricNonSquareL2Pooling3dInt16Test( |
| 1613 | armnn::IWorkloadFactory& workloadFactory, |
| 1614 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 1615 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
| 1616 | const armnn::DataLayout dataLayout) |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 1617 | { |
| 1618 | return AsymmetricNonSquareL2Pooling3dTestCommon<armnn::DataType::QSymmS16>( |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 1619 | workloadFactory, memoryManager, tensorHandleFactory, dataLayout); |
| 1620 | } |
| 1621 | |
| 1622 | LayerTestResult<float, 5> AsymmetricNonSquareL2Pooling3dWithPaddingOnlyPoolTest( |
| 1623 | armnn::IWorkloadFactory& workloadFactory, |
| 1624 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 1625 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
| 1626 | const armnn::DataLayout dataLayout) |
| 1627 | { |
| 1628 | return AsymmetricNonSquareL2Pooling3dWithPaddingOnlyPoolTestCommon<armnn::DataType::Float32>( |
| 1629 | workloadFactory, memoryManager, tensorHandleFactory, dataLayout); |
| 1630 | } |
| 1631 | |
| 1632 | LayerTestResult<uint8_t, 5> AsymmetricNonSquareL2Pooling3dWithPaddingOnlyPoolUint8Test( |
| 1633 | armnn::IWorkloadFactory& workloadFactory, |
| 1634 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 1635 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
| 1636 | const armnn::DataLayout dataLayout) |
| 1637 | { |
| 1638 | return AsymmetricNonSquareL2Pooling3dWithPaddingOnlyPoolTestCommon<armnn::DataType::QAsymmU8>( |
| 1639 | workloadFactory, memoryManager, tensorHandleFactory, dataLayout); |
| 1640 | } |
| 1641 | |
| 1642 | LayerTestResult<int16_t, 5> AsymmetricNonSquareL2Pooling3dWithPaddingOnlyPoolInt16Test( |
| 1643 | armnn::IWorkloadFactory& workloadFactory, |
| 1644 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 1645 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
| 1646 | const armnn::DataLayout dataLayout) |
| 1647 | { |
| 1648 | return AsymmetricNonSquareL2Pooling3dWithPaddingOnlyPoolTestCommon<armnn::DataType::QSymmS16>( |
| 1649 | workloadFactory, memoryManager, tensorHandleFactory, dataLayout); |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 1650 | } |
| 1651 | |
| 1652 | LayerTestResult<float, 5> ComparePooling3dTest( |
| 1653 | armnn::IWorkloadFactory& workloadFactory, |
| 1654 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 1655 | armnn::IWorkloadFactory& refWorkloadFactory, |
| 1656 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
| 1657 | const armnn::ITensorHandleFactory& refTensorHandleFactory, |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 1658 | armnn::PoolingAlgorithm poolingType, |
| 1659 | const armnn::DataLayout dataLayout) |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 1660 | { |
| 1661 | return ComparePooling3dTestCommon<armnn::DataType::Float32>( |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 1662 | workloadFactory, memoryManager, refWorkloadFactory, tensorHandleFactory, refTensorHandleFactory, |
| 1663 | poolingType, dataLayout); |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 1664 | } |
| 1665 | |
| 1666 | LayerTestResult<uint8_t, 5> ComparePooling3dUint8Test( |
| 1667 | armnn::IWorkloadFactory& workloadFactory, |
| 1668 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 1669 | armnn::IWorkloadFactory& refWorkloadFactory, |
| 1670 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
| 1671 | const armnn::ITensorHandleFactory& refTensorHandleFactory, |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 1672 | armnn::PoolingAlgorithm poolingType, |
| 1673 | const armnn::DataLayout dataLayout) |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 1674 | { |
| 1675 | return ComparePooling3dTestCommon<armnn::DataType::QAsymmU8>( |
| 1676 | workloadFactory, memoryManager, refWorkloadFactory, tensorHandleFactory, refTensorHandleFactory, |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 1677 | poolingType, dataLayout, 0.1f, 128); |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 1678 | } |
| 1679 | |
| 1680 | LayerTestResult<int16_t, 5> ComparePooling3dInt16Test( |
| 1681 | armnn::IWorkloadFactory& workloadFactory, |
| 1682 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 1683 | armnn::IWorkloadFactory& refWorkloadFactory, |
| 1684 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
| 1685 | const armnn::ITensorHandleFactory& refTensorHandleFactory, |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 1686 | armnn::PoolingAlgorithm poolingType, |
| 1687 | const armnn::DataLayout dataLayout) |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 1688 | { |
| 1689 | return ComparePooling3dTestCommon<armnn::DataType::QSymmS16>( |
Ryan OShea | bab8fa9 | 2022-03-09 10:29:02 +0000 | [diff] [blame] | 1690 | workloadFactory, memoryManager, refWorkloadFactory, tensorHandleFactory, refTensorHandleFactory, |
| 1691 | poolingType, dataLayout); |
Tamás Nyíri | 7b885b3 | 2021-10-26 14:47:57 +0100 | [diff] [blame] | 1692 | } |