Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1 | // |
Teresa Charlin | fbf0e5b | 2020-08-17 01:01:06 +0100 | [diff] [blame] | 2 | // Copyright © 2017 Arm Ltd and Contributors. All rights reserved. |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3 | // SPDX-License-Identifier: MIT |
| 4 | // |
| 5 | |
| 6 | #include "BatchNormalizationTestImpl.hpp" |
| 7 | |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 8 | #include <QuantizeHelper.hpp> |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 9 | #include <ResolveType.hpp> |
| 10 | |
Jan Eilers | 8eb2560 | 2020-03-09 12:13:48 +0000 | [diff] [blame] | 11 | #include <armnn/utility/IgnoreUnused.hpp> |
Matteo Martincigh | e011d20 | 2019-11-28 11:35:47 +0000 | [diff] [blame] | 12 | #include <armnnUtils/DataLayoutIndexed.hpp> |
| 13 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 14 | #include <backendsCommon/CpuTensorHandle.hpp> |
Matteo Martincigh | e5b8eb9 | 2019-11-28 15:45:42 +0000 | [diff] [blame] | 15 | #include <armnn/backends/IBackendInternal.hpp> |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 16 | #include <backendsCommon/WorkloadFactory.hpp> |
Keith Davis | 33a626f | 2020-08-27 15:38:12 +0100 | [diff] [blame] | 17 | #include <reference/test/RefWorkloadFactoryHelper.hpp> |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 18 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 19 | #include <backendsCommon/test/TensorCopyUtils.hpp> |
| 20 | #include <backendsCommon/test/WorkloadTestUtils.hpp> |
| 21 | |
| 22 | #include <test/TensorHelpers.hpp> |
| 23 | |
| 24 | namespace |
| 25 | { |
| 26 | |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 27 | using namespace armnnUtils; |
| 28 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 29 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
| 30 | LayerTestResult<T, 4> BatchNormTestImpl( |
| 31 | armnn::IWorkloadFactory& workloadFactory, |
| 32 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | 33a626f | 2020-08-27 15:38:12 +0100 | [diff] [blame] | 33 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 34 | const armnn::TensorShape& inputOutputTensorShape, |
| 35 | const std::vector<float>& inputValues, |
| 36 | const std::vector<float>& expectedOutputValues, |
| 37 | float qScale, |
| 38 | int32_t qOffset, |
| 39 | armnn::DataLayout dataLayout) |
| 40 | { |
Jan Eilers | 8eb2560 | 2020-03-09 12:13:48 +0000 | [diff] [blame] | 41 | IgnoreUnused(memoryManager); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 42 | armnn::TensorInfo inputTensorInfo(inputOutputTensorShape, ArmnnType); |
| 43 | armnn::TensorInfo outputTensorInfo(inputOutputTensorShape, ArmnnType); |
| 44 | |
| 45 | armnnUtils::DataLayoutIndexed dataLayoutIndexed(dataLayout); |
| 46 | |
| 47 | armnn::TensorInfo tensorInfo({ inputOutputTensorShape[dataLayoutIndexed.GetChannelsIndex()] }, |
| 48 | ArmnnType); |
| 49 | |
| 50 | // Set quantization parameters if the requested type is a quantized type. |
| 51 | if (armnn::IsQuantizedType<T>()) |
| 52 | { |
| 53 | inputTensorInfo.SetQuantizationScale(qScale); |
| 54 | inputTensorInfo.SetQuantizationOffset(qOffset); |
| 55 | outputTensorInfo.SetQuantizationScale(qScale); |
| 56 | outputTensorInfo.SetQuantizationOffset(qOffset); |
| 57 | tensorInfo.SetQuantizationScale(qScale); |
| 58 | tensorInfo.SetQuantizationOffset(qOffset); |
| 59 | } |
| 60 | |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 61 | auto inputTensor = MakeTensor<T, 4>(inputTensorInfo, QuantizedVector<T>(inputValues, qScale, qOffset)); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 62 | |
| 63 | // These values are per-channel of the input. |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 64 | auto mean = MakeTensor<T, 1>(tensorInfo, QuantizedVector<T>({ 3, -2 }, qScale, qOffset)); |
| 65 | auto variance = MakeTensor<T, 1>(tensorInfo, QuantizedVector<T>({ 4, 9 }, qScale, qOffset)); |
| 66 | auto beta = MakeTensor<T, 1>(tensorInfo, QuantizedVector<T>({ 3, 2 }, qScale, qOffset)); |
| 67 | auto gamma = MakeTensor<T, 1>(tensorInfo, QuantizedVector<T>({ 2, 1 }, qScale, qOffset)); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 68 | |
| 69 | LayerTestResult<T, 4> result(outputTensorInfo); |
| 70 | |
| 71 | result.outputExpected = MakeTensor<T, 4>(inputTensorInfo, |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 72 | QuantizedVector<T>(expectedOutputValues, qScale, qOffset)); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 73 | |
Keith Davis | 33a626f | 2020-08-27 15:38:12 +0100 | [diff] [blame] | 74 | std::unique_ptr<armnn::ITensorHandle> inputHandle = tensorHandleFactory.CreateTensorHandle(inputTensorInfo); |
| 75 | std::unique_ptr<armnn::ITensorHandle> outputHandle = tensorHandleFactory.CreateTensorHandle(outputTensorInfo); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 76 | |
| 77 | armnn::ScopedCpuTensorHandle meanTensor(tensorInfo); |
| 78 | armnn::ScopedCpuTensorHandle varianceTensor(tensorInfo); |
| 79 | armnn::ScopedCpuTensorHandle betaTensor(tensorInfo); |
| 80 | armnn::ScopedCpuTensorHandle gammaTensor(tensorInfo); |
| 81 | |
| 82 | armnn::BatchNormalizationQueueDescriptor descriptor; |
| 83 | descriptor.m_Mean = &meanTensor; |
| 84 | descriptor.m_Variance = &varianceTensor; |
| 85 | descriptor.m_Beta = &betaTensor; |
| 86 | descriptor.m_Gamma = &gammaTensor; |
| 87 | descriptor.m_Parameters.m_Eps = 0.0f; |
| 88 | descriptor.m_Parameters.m_DataLayout = dataLayout; |
| 89 | armnn::WorkloadInfo info; |
| 90 | |
| 91 | AllocateAndCopyDataToITensorHandle(&meanTensor, &mean[0]); |
| 92 | AllocateAndCopyDataToITensorHandle(&varianceTensor, &variance[0]); |
| 93 | AllocateAndCopyDataToITensorHandle(&betaTensor, &beta[0]); |
| 94 | AllocateAndCopyDataToITensorHandle(&gammaTensor, &gamma[0]); |
| 95 | |
| 96 | AddInputToWorkload(descriptor, info, inputTensorInfo, inputHandle.get()); |
| 97 | AddOutputToWorkload(descriptor, info, outputTensorInfo, outputHandle.get()); |
| 98 | |
| 99 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateBatchNormalization(descriptor, info); |
| 100 | |
| 101 | inputHandle->Allocate(); |
| 102 | outputHandle->Allocate(); |
| 103 | |
| 104 | CopyDataToITensorHandle(inputHandle.get(), &inputTensor[0][0][0][0]); |
| 105 | |
| 106 | workload->Execute(); |
| 107 | |
| 108 | CopyDataFromITensorHandle(&result.output[0][0][0][0], outputHandle.get()); |
| 109 | |
| 110 | return result; |
| 111 | } |
| 112 | |
| 113 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
| 114 | LayerTestResult<T,4> BatchNormTestNhwcImpl( |
| 115 | armnn::IWorkloadFactory& workloadFactory, |
| 116 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | 33a626f | 2020-08-27 15:38:12 +0100 | [diff] [blame] | 117 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 118 | float qScale, |
| 119 | int32_t qOffset) |
| 120 | { |
Jan Eilers | 8eb2560 | 2020-03-09 12:13:48 +0000 | [diff] [blame] | 121 | IgnoreUnused(memoryManager); |
Derek Lamberti | c374ff0 | 2019-12-10 21:57:35 +0000 | [diff] [blame] | 122 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 123 | const unsigned int width = 2; |
| 124 | const unsigned int height = 3; |
| 125 | const unsigned int channels = 2; |
| 126 | const unsigned int num = 1; |
| 127 | |
| 128 | armnn::TensorInfo inputTensorInfo({num, height, width, channels}, ArmnnType); |
| 129 | armnn::TensorInfo outputTensorInfo({num, height, width, channels}, ArmnnType); |
| 130 | armnn::TensorInfo tensorInfo({channels}, ArmnnType); |
| 131 | |
| 132 | // Set quantization parameters if the requested type is a quantized type. |
| 133 | if(armnn::IsQuantizedType<T>()) |
| 134 | { |
| 135 | inputTensorInfo.SetQuantizationScale(qScale); |
| 136 | inputTensorInfo.SetQuantizationOffset(qOffset); |
| 137 | outputTensorInfo.SetQuantizationScale(qScale); |
| 138 | outputTensorInfo.SetQuantizationOffset(qOffset); |
| 139 | tensorInfo.SetQuantizationScale(qScale); |
| 140 | tensorInfo.SetQuantizationOffset(qOffset); |
| 141 | } |
| 142 | |
| 143 | auto input = MakeTensor<T, 4>(inputTensorInfo, |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 144 | QuantizedVector<T>( |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 145 | { |
| 146 | 1.f, 1.f, 4.f, 1.f, |
| 147 | 4.f, 4.f, 2.f, 1.f, |
| 148 | 1.f, -2.f, 6.f, 4.f |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 149 | }, |
| 150 | qScale, qOffset)); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 151 | // These values are per-channel of the input. |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 152 | auto mean = MakeTensor<T, 1>(tensorInfo, QuantizedVector<T>({ 3, -2 }, qScale, qOffset)); |
| 153 | auto variance = MakeTensor<T, 1>(tensorInfo, QuantizedVector<T>({ 4, 9 }, qScale, qOffset)); |
| 154 | auto beta = MakeTensor<T, 1>(tensorInfo, QuantizedVector<T>({ 3, 2 }, qScale, qOffset)); |
| 155 | auto gamma = MakeTensor<T, 1>(tensorInfo, QuantizedVector<T>({ 2, 1 }, qScale, qOffset)); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 156 | LayerTestResult<T,4> ret(outputTensorInfo); |
| 157 | |
Keith Davis | 33a626f | 2020-08-27 15:38:12 +0100 | [diff] [blame] | 158 | std::unique_ptr<armnn::ITensorHandle> inputHandle = tensorHandleFactory.CreateTensorHandle(inputTensorInfo); |
| 159 | std::unique_ptr<armnn::ITensorHandle> outputHandle = tensorHandleFactory.CreateTensorHandle(outputTensorInfo); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 160 | |
| 161 | armnn::BatchNormalizationQueueDescriptor data; |
| 162 | armnn::WorkloadInfo info; |
| 163 | armnn::ScopedCpuTensorHandle meanTensor(tensorInfo); |
| 164 | armnn::ScopedCpuTensorHandle varianceTensor(tensorInfo); |
| 165 | armnn::ScopedCpuTensorHandle betaTensor(tensorInfo); |
| 166 | armnn::ScopedCpuTensorHandle gammaTensor(tensorInfo); |
| 167 | |
| 168 | AllocateAndCopyDataToITensorHandle(&meanTensor, &mean[0]); |
| 169 | AllocateAndCopyDataToITensorHandle(&varianceTensor, &variance[0]); |
| 170 | AllocateAndCopyDataToITensorHandle(&betaTensor, &beta[0]); |
| 171 | AllocateAndCopyDataToITensorHandle(&gammaTensor, &gamma[0]); |
| 172 | |
| 173 | AddInputToWorkload(data, info, inputTensorInfo, inputHandle.get()); |
| 174 | AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get()); |
| 175 | data.m_Mean = &meanTensor; |
| 176 | data.m_Variance = &varianceTensor; |
| 177 | data.m_Beta = &betaTensor; |
| 178 | data.m_Gamma = &gammaTensor; |
| 179 | data.m_Parameters.m_Eps = 0.0f; |
| 180 | data.m_Parameters.m_DataLayout = armnn::DataLayout::NHWC; |
| 181 | |
| 182 | // For each channel: |
| 183 | // substract mean, divide by standard deviation (with an epsilon to avoid div by 0), |
| 184 | // multiply by gamma and add beta |
| 185 | ret.outputExpected = MakeTensor<T, 4>(outputTensorInfo, |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 186 | QuantizedVector<T>( |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 187 | { |
| 188 | 1.f, 3.f, 4.f, 3.f, |
| 189 | 4.f, 4.f, 2.f, 3.f, |
| 190 | 1.f, 2.f, 6.f, 4.f |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 191 | }, |
| 192 | qScale, qOffset)); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 193 | |
| 194 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateBatchNormalization(data, info); |
| 195 | |
| 196 | inputHandle->Allocate(); |
| 197 | outputHandle->Allocate(); |
| 198 | |
| 199 | CopyDataToITensorHandle(inputHandle.get(), &input[0][0][0][0]); |
| 200 | |
| 201 | workload->Execute(); |
| 202 | |
| 203 | CopyDataFromITensorHandle(&ret.output[0][0][0][0], outputHandle.get()); |
| 204 | |
| 205 | return ret; |
| 206 | } |
| 207 | |
| 208 | } // anonymous namespace |
| 209 | |
Matthew Jackson | 9bff144 | 2019-09-12 09:08:23 +0100 | [diff] [blame] | 210 | LayerTestResult<float, 4> BatchNormFloat32Test( |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 211 | armnn::IWorkloadFactory& workloadFactory, |
Keith Davis | 33a626f | 2020-08-27 15:38:12 +0100 | [diff] [blame] | 212 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 213 | const armnn::ITensorHandleFactory& tensorHandleFactory) |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 214 | { |
| 215 | // BatchSize: 1 |
| 216 | // Channels: 2 |
| 217 | // Height: 3 |
| 218 | // Width: 2 |
| 219 | |
| 220 | const armnn::TensorShape inputOutputShape{ 1, 2, 3, 2 }; |
| 221 | std::vector<float> inputValues |
| 222 | { |
| 223 | // Batch 0, Channel 0, Height (3) x Width (2) |
| 224 | 1.f, 4.f, |
| 225 | 4.f, 2.f, |
| 226 | 1.f, 6.f, |
| 227 | |
| 228 | // Batch 0, Channel 1, Height (3) x Width (2) |
| 229 | 1.f, 1.f, |
| 230 | 4.f, 1.f, |
| 231 | -2.f, 4.f |
| 232 | }; |
| 233 | std::vector<float> expectedOutputValues |
| 234 | { |
| 235 | // Batch 0, Channel 0, Height (3) x Width (2) |
| 236 | 1.f, 4.f, |
| 237 | 4.f, 2.f, |
| 238 | 1.f, 6.f, |
| 239 | |
| 240 | // Batch 0, Channel 1, Height (3) x Width (2) |
| 241 | 3.f, 3.f, |
| 242 | 4.f, 3.f, |
| 243 | 2.f, 4.f |
| 244 | }; |
| 245 | |
| 246 | return BatchNormTestImpl<armnn::DataType::Float32>( |
| 247 | workloadFactory, |
| 248 | memoryManager, |
Keith Davis | 33a626f | 2020-08-27 15:38:12 +0100 | [diff] [blame] | 249 | tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 250 | inputOutputShape, |
| 251 | inputValues, |
| 252 | expectedOutputValues, |
| 253 | 0.f, |
| 254 | 0, |
| 255 | armnn::DataLayout::NCHW); |
| 256 | } |
| 257 | |
Matthew Jackson | 9bff144 | 2019-09-12 09:08:23 +0100 | [diff] [blame] | 258 | LayerTestResult<float, 4> BatchNormFloat32NhwcTest( |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 259 | armnn::IWorkloadFactory& workloadFactory, |
Keith Davis | 33a626f | 2020-08-27 15:38:12 +0100 | [diff] [blame] | 260 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 261 | const armnn::ITensorHandleFactory& tensorHandleFactory) |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 262 | { |
| 263 | // BatchSize: 1 |
| 264 | // Height: 3 |
| 265 | // Width: 2 |
| 266 | // Channels: 2 |
| 267 | |
| 268 | const armnn::TensorShape inputOutputShape{ 1, 3, 2, 2 }; |
| 269 | std::vector<float> inputValues |
| 270 | { |
| 271 | // Batch 0, Height 0, Width (2) x Channel (2) |
| 272 | 1.f, 1.f, |
| 273 | 4.f, 1.f, |
| 274 | |
| 275 | // Batch 0, Height 1, Width (2) x Channel (2) |
| 276 | 4.f, 4.f, |
| 277 | 2.f, 1.f, |
| 278 | |
| 279 | // Batch 0, Height 2, Width (2) x Channel (2) |
| 280 | 1.f, -2.f, |
| 281 | 6.f, 4.f |
| 282 | }; |
| 283 | std::vector<float> expectedOutputValues |
| 284 | { |
| 285 | // Batch 0, Height 0, Width (2) x Channel (2) |
| 286 | 1.f, 3.f, |
| 287 | 4.f, 3.f, |
| 288 | |
| 289 | // Batch 0, Height 1, Width (2) x Channel (2) |
| 290 | 4.f, 4.f, |
| 291 | 2.f, 3.f, |
| 292 | |
| 293 | // Batch 0, Height 2, Width (2) x Channel (2) |
| 294 | 1.f, 2.f, |
| 295 | 6.f, 4.f |
| 296 | }; |
| 297 | |
| 298 | return BatchNormTestImpl<armnn::DataType::Float32>( |
| 299 | workloadFactory, |
| 300 | memoryManager, |
Keith Davis | 33a626f | 2020-08-27 15:38:12 +0100 | [diff] [blame] | 301 | tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 302 | inputOutputShape, |
| 303 | inputValues, |
| 304 | expectedOutputValues, |
| 305 | 0.f, |
| 306 | 0, |
| 307 | armnn::DataLayout::NHWC); |
| 308 | } |
| 309 | |
Matthew Jackson | 9bff144 | 2019-09-12 09:08:23 +0100 | [diff] [blame] | 310 | LayerTestResult<armnn::Half, 4> BatchNormFloat16Test( |
| 311 | armnn::IWorkloadFactory& workloadFactory, |
Keith Davis | 33a626f | 2020-08-27 15:38:12 +0100 | [diff] [blame] | 312 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 313 | const armnn::ITensorHandleFactory& tensorHandleFactory) |
Matthew Jackson | 9bff144 | 2019-09-12 09:08:23 +0100 | [diff] [blame] | 314 | { |
| 315 | // BatchSize: 1 |
| 316 | // Channels: 2 |
| 317 | // Height: 3 |
| 318 | // Width: 2 |
| 319 | |
| 320 | const armnn::TensorShape inputOutputShape{ 1, 2, 3, 2 }; |
| 321 | std::vector<float> inputValues |
| 322 | { |
| 323 | // Batch 0, Channel 0, Height (3) x Width (2) |
| 324 | 1.f, 4.f, |
| 325 | 4.f, 2.f, |
| 326 | 1.f, 6.f, |
| 327 | |
| 328 | // Batch 0, Channel 1, Height (3) x Width (2) |
| 329 | 1.f, 1.f, |
| 330 | 4.f, 1.f, |
| 331 | -2.f, 4.f |
| 332 | }; |
| 333 | std::vector<float> expectedOutputValues |
| 334 | { |
| 335 | // Batch 0, Channel 0, Height (3) x Width (2) |
| 336 | 1.f, 4.f, |
| 337 | 4.f, 2.f, |
| 338 | 1.f, 6.f, |
| 339 | |
| 340 | // Batch 0, Channel 1, Height (3) x Width (2) |
| 341 | 3.f, 3.f, |
| 342 | 4.f, 3.f, |
| 343 | 2.f, 4.f |
| 344 | }; |
| 345 | |
| 346 | return BatchNormTestImpl<armnn::DataType::Float16>( |
| 347 | workloadFactory, |
| 348 | memoryManager, |
Keith Davis | 33a626f | 2020-08-27 15:38:12 +0100 | [diff] [blame] | 349 | tensorHandleFactory, |
Matthew Jackson | 9bff144 | 2019-09-12 09:08:23 +0100 | [diff] [blame] | 350 | inputOutputShape, |
| 351 | inputValues, |
| 352 | expectedOutputValues, |
| 353 | 0.f, |
| 354 | 0, |
| 355 | armnn::DataLayout::NCHW); |
| 356 | } |
| 357 | |
| 358 | LayerTestResult<armnn::Half, 4> BatchNormFloat16NhwcTest( |
| 359 | armnn::IWorkloadFactory& workloadFactory, |
Keith Davis | 33a626f | 2020-08-27 15:38:12 +0100 | [diff] [blame] | 360 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 361 | const armnn::ITensorHandleFactory& tensorHandleFactory) |
Matthew Jackson | 9bff144 | 2019-09-12 09:08:23 +0100 | [diff] [blame] | 362 | { |
| 363 | // BatchSize: 1 |
| 364 | // Height: 3 |
| 365 | // Width: 2 |
| 366 | // Channels: 2 |
| 367 | |
| 368 | const armnn::TensorShape inputOutputShape{ 1, 3, 2, 2 }; |
| 369 | std::vector<float> inputValues |
| 370 | { |
| 371 | // Batch 0, Height 0, Width (2) x Channel (2) |
| 372 | 1.f, 1.f, |
| 373 | 4.f, 1.f, |
| 374 | |
| 375 | // Batch 0, Height 1, Width (2) x Channel (2) |
| 376 | 4.f, 4.f, |
| 377 | 2.f, 1.f, |
| 378 | |
| 379 | // Batch 0, Height 2, Width (2) x Channel (2) |
| 380 | 1.f, -2.f, |
| 381 | 6.f, 4.f |
| 382 | }; |
| 383 | std::vector<float> expectedOutputValues |
| 384 | { |
| 385 | // Batch 0, Height 0, Width (2) x Channel (2) |
| 386 | 1.f, 3.f, |
| 387 | 4.f, 3.f, |
| 388 | |
| 389 | // Batch 0, Height 1, Width (2) x Channel (2) |
| 390 | 4.f, 4.f, |
| 391 | 2.f, 3.f, |
| 392 | |
| 393 | // Batch 0, Height 2, Width (2) x Channel (2) |
| 394 | 1.f, 2.f, |
| 395 | 6.f, 4.f |
| 396 | }; |
| 397 | |
| 398 | return BatchNormTestImpl<armnn::DataType::Float16>( |
| 399 | workloadFactory, |
| 400 | memoryManager, |
Keith Davis | 33a626f | 2020-08-27 15:38:12 +0100 | [diff] [blame] | 401 | tensorHandleFactory, |
Matthew Jackson | 9bff144 | 2019-09-12 09:08:23 +0100 | [diff] [blame] | 402 | inputOutputShape, |
| 403 | inputValues, |
| 404 | expectedOutputValues, |
| 405 | 0.f, |
| 406 | 0, |
| 407 | armnn::DataLayout::NHWC); |
| 408 | } |
| 409 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 410 | LayerTestResult<uint8_t, 4> BatchNormUint8Test( |
| 411 | armnn::IWorkloadFactory& workloadFactory, |
Keith Davis | 33a626f | 2020-08-27 15:38:12 +0100 | [diff] [blame] | 412 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 413 | const armnn::ITensorHandleFactory& tensorHandleFactory) |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 414 | { |
| 415 | // BatchSize: 1 |
| 416 | // Channels: 2 |
| 417 | // Height: 3 |
| 418 | // Width: 2 |
| 419 | |
| 420 | const armnn::TensorShape inputOutputShape{ 1, 2, 3, 2 }; |
| 421 | std::vector<float> inputValues |
| 422 | { |
| 423 | // Batch 0, Channel 0, Height (3) x Width (2) |
| 424 | 1.f, 4.f, |
| 425 | 4.f, 2.f, |
| 426 | 1.f, 6.f, |
| 427 | |
| 428 | // Batch 0, Channel 1, Height (3) x Width (2) |
| 429 | 1.f, 1.f, |
| 430 | 4.f, 1.f, |
| 431 | -2.f, 4.f |
| 432 | }; |
| 433 | std::vector<float> expectedOutputValues |
| 434 | { |
| 435 | // Batch 0, Channel 0, Height (3) x Width (2) |
| 436 | 1.f, 4.f, |
| 437 | 4.f, 2.f, |
| 438 | 1.f, 6.f, |
| 439 | |
| 440 | // Batch 0, Channel 1, Height (3) x Width (2) |
| 441 | 3.f, 3.f, |
| 442 | 4.f, 3.f, |
| 443 | 2.f, 4.f |
| 444 | }; |
| 445 | |
Derek Lamberti | f90c56d | 2020-01-10 17:14:08 +0000 | [diff] [blame] | 446 | return BatchNormTestImpl<armnn::DataType::QAsymmU8>( |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 447 | workloadFactory, |
| 448 | memoryManager, |
Keith Davis | 33a626f | 2020-08-27 15:38:12 +0100 | [diff] [blame] | 449 | tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 450 | inputOutputShape, |
| 451 | inputValues, |
| 452 | expectedOutputValues, |
| 453 | 1.f / 20.f, |
| 454 | 50, |
| 455 | armnn::DataLayout::NCHW); |
| 456 | } |
| 457 | |
| 458 | LayerTestResult<uint8_t, 4> BatchNormUint8NhwcTest( |
| 459 | armnn::IWorkloadFactory& workloadFactory, |
Keith Davis | 33a626f | 2020-08-27 15:38:12 +0100 | [diff] [blame] | 460 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 461 | const armnn::ITensorHandleFactory& tensorHandleFactory) |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 462 | { |
| 463 | // BatchSize: 1 |
| 464 | // Height: 3 |
| 465 | // Width: 2 |
| 466 | // Channels: 2 |
| 467 | |
| 468 | const armnn::TensorShape inputOutputShape{ 1, 3, 2, 2 }; |
| 469 | std::vector<float> inputValues |
| 470 | { |
| 471 | // Batch 0, Height 0, Width (2) x Channel (2) |
| 472 | 1.f, 1.f, |
| 473 | 4.f, 1.f, |
| 474 | |
| 475 | // Batch 0, Height 1, Width (2) x Channel (2) |
| 476 | 4.f, 4.f, |
| 477 | 2.f, 1.f, |
| 478 | |
| 479 | // Batch 0, Height 2, Width (2) x Channel (2) |
| 480 | 1.f, -2.f, |
| 481 | 6.f, 4.f |
| 482 | }; |
| 483 | std::vector<float> expectedOutputValues |
| 484 | { |
| 485 | // Batch 0, Height 0, Width (2) x Channel (2) |
| 486 | 1.f, 3.f, |
| 487 | 4.f, 3.f, |
| 488 | |
| 489 | // Batch 0, Height 1, Width (2) x Channel (2) |
| 490 | 4.f, 4.f, |
| 491 | 2.f, 3.f, |
| 492 | |
| 493 | // Batch 0, Height 2, Width (2) x Channel (2) |
| 494 | 1.f, 2.f, |
| 495 | 6.f, 4.f |
| 496 | }; |
| 497 | |
Derek Lamberti | f90c56d | 2020-01-10 17:14:08 +0000 | [diff] [blame] | 498 | return BatchNormTestImpl<armnn::DataType::QAsymmU8>( |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 499 | workloadFactory, |
| 500 | memoryManager, |
Keith Davis | 33a626f | 2020-08-27 15:38:12 +0100 | [diff] [blame] | 501 | tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 502 | inputOutputShape, inputValues, expectedOutputValues, |
| 503 | 1.f/20.f, 50, armnn::DataLayout::NHWC); |
| 504 | } |
| 505 | |
| 506 | LayerTestResult<int16_t, 4> BatchNormInt16Test( |
| 507 | armnn::IWorkloadFactory& workloadFactory, |
Keith Davis | 33a626f | 2020-08-27 15:38:12 +0100 | [diff] [blame] | 508 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 509 | const armnn::ITensorHandleFactory& tensorHandleFactory) |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 510 | { |
| 511 | // BatchSize: 1 |
| 512 | // Channels: 2 |
| 513 | // Height: 3 |
| 514 | // Width: 2 |
| 515 | |
| 516 | const armnn::TensorShape inputOutputShape{ 1, 2, 3, 2 }; |
| 517 | std::vector<float> inputValues |
| 518 | { |
| 519 | // Batch 0, Channel 0, Height (3) x Width (2) |
| 520 | 1.f, 4.f, |
| 521 | 4.f, 2.f, |
| 522 | 1.f, 6.f, |
| 523 | |
| 524 | // Batch 0, Channel 1, Height (3) x Width (2) |
| 525 | 1.f, 1.f, |
| 526 | 4.f, 1.f, |
| 527 | -2.f, 4.f |
| 528 | }; |
| 529 | std::vector<float> expectedOutputValues |
| 530 | { |
| 531 | // Batch 0, Channel 0, Height (3) x Width (2) |
| 532 | 1.f, 4.f, |
| 533 | 4.f, 2.f, |
| 534 | 1.f, 6.f, |
| 535 | |
| 536 | // Batch 0, Channel 1, Height (3) x Width (2) |
| 537 | 3.f, 3.f, |
| 538 | 4.f, 3.f, |
| 539 | 2.f, 4.f |
| 540 | }; |
| 541 | |
Derek Lamberti | f90c56d | 2020-01-10 17:14:08 +0000 | [diff] [blame] | 542 | return BatchNormTestImpl<armnn::DataType::QSymmS16>( |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 543 | workloadFactory, |
| 544 | memoryManager, |
Keith Davis | 33a626f | 2020-08-27 15:38:12 +0100 | [diff] [blame] | 545 | tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 546 | inputOutputShape, |
| 547 | inputValues, |
| 548 | expectedOutputValues, |
| 549 | 1.f / 20.f, |
| 550 | 50, |
| 551 | armnn::DataLayout::NCHW); |
| 552 | } |
| 553 | |
| 554 | LayerTestResult<int16_t, 4> BatchNormInt16NhwcTest( |
| 555 | armnn::IWorkloadFactory& workloadFactory, |
Keith Davis | 33a626f | 2020-08-27 15:38:12 +0100 | [diff] [blame] | 556 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 557 | const armnn::ITensorHandleFactory& tensorHandleFactory) |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 558 | { |
| 559 | // BatchSize: 1 |
| 560 | // Height: 3 |
| 561 | // Width: 2 |
| 562 | // Channels: 2 |
| 563 | |
| 564 | const armnn::TensorShape inputOutputShape{ 1, 3, 2, 2 }; |
| 565 | std::vector<float> inputValues |
| 566 | { |
| 567 | // Batch 0, Height 0, Width (2) x Channel (2) |
| 568 | 1.f, 1.f, |
| 569 | 4.f, 1.f, |
| 570 | |
| 571 | // Batch 0, Height 1, Width (2) x Channel (2) |
| 572 | 4.f, 4.f, |
| 573 | 2.f, 1.f, |
| 574 | |
| 575 | // Batch 0, Height 2, Width (2) x Channel (2) |
| 576 | 1.f, -2.f, |
| 577 | 6.f, 4.f |
| 578 | }; |
| 579 | std::vector<float> expectedOutputValues |
| 580 | { |
| 581 | // Batch 0, Height 0, Width (2) x Channel (2) |
| 582 | 1.f, 3.f, |
| 583 | 4.f, 3.f, |
| 584 | |
| 585 | // Batch 0, Height 1, Width (2) x Channel (2) |
| 586 | 4.f, 4.f, |
| 587 | 2.f, 3.f, |
| 588 | |
| 589 | // Batch 0, Height 2, Width (2) x Channel (2) |
| 590 | 1.f, 2.f, |
| 591 | 6.f, 4.f |
| 592 | }; |
| 593 | |
Derek Lamberti | f90c56d | 2020-01-10 17:14:08 +0000 | [diff] [blame] | 594 | return BatchNormTestImpl<armnn::DataType::QSymmS16>( |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 595 | workloadFactory, |
| 596 | memoryManager, |
Keith Davis | 33a626f | 2020-08-27 15:38:12 +0100 | [diff] [blame] | 597 | tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 598 | inputOutputShape, |
| 599 | inputValues, |
| 600 | expectedOutputValues, |
| 601 | 1.f / 20.f, |
| 602 | 50, |
| 603 | armnn::DataLayout::NHWC); |
| 604 | } |
| 605 | |
| 606 | LayerTestResult<float,4> CompareBatchNormTest( |
| 607 | armnn::IWorkloadFactory& workloadFactory, |
| 608 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | 33a626f | 2020-08-27 15:38:12 +0100 | [diff] [blame] | 609 | armnn::IWorkloadFactory& refWorkloadFactory, |
| 610 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
| 611 | const armnn::ITensorHandleFactory& refTensorHandleFactory) |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 612 | { |
Jan Eilers | 8eb2560 | 2020-03-09 12:13:48 +0000 | [diff] [blame] | 613 | IgnoreUnused(memoryManager); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 614 | const unsigned int width = 2; |
| 615 | const unsigned int height = 3; |
| 616 | const unsigned int channels = 5; |
| 617 | const unsigned int batchSize = 3; |
| 618 | |
| 619 | armnn::TensorInfo inputTensorInfo; |
| 620 | armnn::TensorInfo outputTensorInfo; |
| 621 | armnn::TensorInfo tensorInfo; |
| 622 | |
| 623 | constexpr unsigned int shape[] = {batchSize, channels, height, width}; |
| 624 | constexpr unsigned int tensorShape[] = {channels}; |
| 625 | |
| 626 | inputTensorInfo = armnn::TensorInfo(4, shape, armnn::DataType::Float32); |
| 627 | outputTensorInfo = armnn::TensorInfo(4, shape, armnn::DataType::Float32); |
| 628 | tensorInfo = armnn::TensorInfo(1, tensorShape, armnn::DataType::Float32); |
| 629 | |
| 630 | auto input = MakeRandomTensor<float, 4>(inputTensorInfo, 21312); |
| 631 | |
| 632 | auto mean = MakeRandomTensor<float, 1>(tensorInfo, 123); |
| 633 | auto variance = MakeRandomTensor<float, 1>(tensorInfo, 234, 0.0f); |
| 634 | auto beta = MakeRandomTensor<float, 1>(tensorInfo, 123); |
| 635 | auto gamma = MakeRandomTensor<float, 1>(tensorInfo, 345); |
| 636 | |
| 637 | LayerTestResult<float,4> ret(outputTensorInfo); |
| 638 | |
Keith Davis | 33a626f | 2020-08-27 15:38:12 +0100 | [diff] [blame] | 639 | std::unique_ptr<armnn::ITensorHandle> inputHandle = tensorHandleFactory.CreateTensorHandle(inputTensorInfo); |
| 640 | std::unique_ptr<armnn::ITensorHandle> outputHandle = tensorHandleFactory.CreateTensorHandle(outputTensorInfo); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 641 | |
Keith Davis | 33a626f | 2020-08-27 15:38:12 +0100 | [diff] [blame] | 642 | std::unique_ptr<armnn::ITensorHandle> inputHandleRef = refTensorHandleFactory.CreateTensorHandle(inputTensorInfo); |
| 643 | std::unique_ptr<armnn::ITensorHandle> outputHandleRef = refTensorHandleFactory.CreateTensorHandle(outputTensorInfo); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 644 | |
| 645 | armnn::BatchNormalizationQueueDescriptor data; |
| 646 | armnn::WorkloadInfo info; |
| 647 | armnn::ScopedCpuTensorHandle meanTensor(tensorInfo); |
| 648 | armnn::ScopedCpuTensorHandle varianceTensor(tensorInfo); |
| 649 | armnn::ScopedCpuTensorHandle betaTensor(tensorInfo); |
| 650 | armnn::ScopedCpuTensorHandle gammaTensor(tensorInfo); |
| 651 | |
| 652 | AllocateAndCopyDataToITensorHandle(&meanTensor, &mean[0]); |
| 653 | AllocateAndCopyDataToITensorHandle(&varianceTensor, &variance[0]); |
| 654 | AllocateAndCopyDataToITensorHandle(&betaTensor, &beta[0]); |
| 655 | AllocateAndCopyDataToITensorHandle(&gammaTensor, &gamma[0]); |
| 656 | |
| 657 | AddInputToWorkload(data, info, inputTensorInfo, inputHandle.get()); |
| 658 | AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get()); |
| 659 | data.m_Mean = &meanTensor; |
| 660 | data.m_Variance = &varianceTensor; |
| 661 | data.m_Beta = &betaTensor; |
| 662 | data.m_Gamma = &gammaTensor; |
| 663 | data.m_Parameters.m_Eps = 0.01f; |
| 664 | |
| 665 | armnn::BatchNormalizationQueueDescriptor refData = data; |
| 666 | armnn::WorkloadInfo refInfo = info; |
| 667 | SetWorkloadInput(refData, refInfo, 0, inputTensorInfo, inputHandleRef.get()); |
| 668 | SetWorkloadOutput(refData, refInfo, 0, outputTensorInfo, outputHandleRef.get()); |
| 669 | |
| 670 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateBatchNormalization(data, info); |
| 671 | std::unique_ptr<armnn::IWorkload> workloadRef = refWorkloadFactory.CreateBatchNormalization(refData, refInfo); |
| 672 | |
| 673 | inputHandle->Allocate(); |
| 674 | outputHandle->Allocate(); |
| 675 | inputHandleRef->Allocate(); |
| 676 | outputHandleRef->Allocate(); |
| 677 | |
| 678 | CopyDataToITensorHandle(inputHandle.get(), &input[0][0][0][0]); |
| 679 | CopyDataToITensorHandle(inputHandleRef.get(), &input[0][0][0][0]); |
| 680 | |
| 681 | workload->PostAllocationConfigure(); |
| 682 | workload->Execute(); |
| 683 | workloadRef->PostAllocationConfigure(); |
| 684 | workloadRef->Execute(); |
| 685 | |
| 686 | CopyDataFromITensorHandle(&ret.output[0][0][0][0], outputHandle.get()); |
| 687 | CopyDataFromITensorHandle(&ret.outputExpected[0][0][0][0], outputHandleRef.get()); |
| 688 | |
| 689 | return ret; |
| 690 | } |