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 | |
James Conroy | 1f58f03 | 2021-04-27 17:13:27 +0100 | [diff] [blame] | 14 | #include <backendsCommon/TensorHandle.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 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 61 | auto inputTensor = 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. |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 64 | auto mean = QuantizedVector<T>({ 3, -2 }, qScale, qOffset); |
| 65 | auto variance = QuantizedVector<T>({ 4, 9 }, qScale, qOffset); |
| 66 | auto beta = QuantizedVector<T>({ 3, 2 }, qScale, qOffset); |
| 67 | auto gamma = QuantizedVector<T>({ 2, 1 }, qScale, qOffset); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 68 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 69 | std::vector<T> actualOutput(outputTensorInfo.GetNumElements()); |
| 70 | std::vector<T> expectedOutput = QuantizedVector<T>(expectedOutputValues, qScale, qOffset); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 71 | |
Keith Davis | 33a626f | 2020-08-27 15:38:12 +0100 | [diff] [blame] | 72 | std::unique_ptr<armnn::ITensorHandle> inputHandle = tensorHandleFactory.CreateTensorHandle(inputTensorInfo); |
| 73 | std::unique_ptr<armnn::ITensorHandle> outputHandle = tensorHandleFactory.CreateTensorHandle(outputTensorInfo); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 74 | |
James Conroy | 1f58f03 | 2021-04-27 17:13:27 +0100 | [diff] [blame] | 75 | armnn::ScopedTensorHandle meanTensor(tensorInfo); |
| 76 | armnn::ScopedTensorHandle varianceTensor(tensorInfo); |
| 77 | armnn::ScopedTensorHandle betaTensor(tensorInfo); |
| 78 | armnn::ScopedTensorHandle gammaTensor(tensorInfo); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 79 | |
| 80 | armnn::BatchNormalizationQueueDescriptor descriptor; |
| 81 | descriptor.m_Mean = &meanTensor; |
| 82 | descriptor.m_Variance = &varianceTensor; |
| 83 | descriptor.m_Beta = &betaTensor; |
| 84 | descriptor.m_Gamma = &gammaTensor; |
| 85 | descriptor.m_Parameters.m_Eps = 0.0f; |
| 86 | descriptor.m_Parameters.m_DataLayout = dataLayout; |
| 87 | armnn::WorkloadInfo info; |
| 88 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 89 | AllocateAndCopyDataToITensorHandle(&meanTensor, mean.data()); |
| 90 | AllocateAndCopyDataToITensorHandle(&varianceTensor, variance.data()); |
| 91 | AllocateAndCopyDataToITensorHandle(&betaTensor, beta.data()); |
| 92 | AllocateAndCopyDataToITensorHandle(&gammaTensor, gamma.data()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 93 | |
| 94 | AddInputToWorkload(descriptor, info, inputTensorInfo, inputHandle.get()); |
| 95 | AddOutputToWorkload(descriptor, info, outputTensorInfo, outputHandle.get()); |
| 96 | |
| 97 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateBatchNormalization(descriptor, info); |
| 98 | |
| 99 | inputHandle->Allocate(); |
| 100 | outputHandle->Allocate(); |
| 101 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 102 | CopyDataToITensorHandle(inputHandle.get(), inputTensor.data()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 103 | |
| 104 | workload->Execute(); |
| 105 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 106 | CopyDataFromITensorHandle(actualOutput.data(), outputHandle.get()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 107 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 108 | return LayerTestResult<T, 4>(actualOutput, |
| 109 | expectedOutput, |
| 110 | outputHandle->GetShape(), |
| 111 | outputTensorInfo.GetShape()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 112 | } |
| 113 | |
| 114 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
| 115 | LayerTestResult<T,4> BatchNormTestNhwcImpl( |
| 116 | armnn::IWorkloadFactory& workloadFactory, |
| 117 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | 33a626f | 2020-08-27 15:38:12 +0100 | [diff] [blame] | 118 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 119 | float qScale, |
| 120 | int32_t qOffset) |
| 121 | { |
Jan Eilers | 8eb2560 | 2020-03-09 12:13:48 +0000 | [diff] [blame] | 122 | IgnoreUnused(memoryManager); |
Derek Lamberti | c374ff0 | 2019-12-10 21:57:35 +0000 | [diff] [blame] | 123 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 124 | const unsigned int width = 2; |
| 125 | const unsigned int height = 3; |
| 126 | const unsigned int channels = 2; |
| 127 | const unsigned int num = 1; |
| 128 | |
| 129 | armnn::TensorInfo inputTensorInfo({num, height, width, channels}, ArmnnType); |
| 130 | armnn::TensorInfo outputTensorInfo({num, height, width, channels}, ArmnnType); |
| 131 | armnn::TensorInfo tensorInfo({channels}, ArmnnType); |
| 132 | |
| 133 | // Set quantization parameters if the requested type is a quantized type. |
| 134 | if(armnn::IsQuantizedType<T>()) |
| 135 | { |
| 136 | inputTensorInfo.SetQuantizationScale(qScale); |
| 137 | inputTensorInfo.SetQuantizationOffset(qOffset); |
| 138 | outputTensorInfo.SetQuantizationScale(qScale); |
| 139 | outputTensorInfo.SetQuantizationOffset(qOffset); |
| 140 | tensorInfo.SetQuantizationScale(qScale); |
| 141 | tensorInfo.SetQuantizationOffset(qOffset); |
| 142 | } |
| 143 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 144 | auto input = 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 | }, |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 150 | qScale, qOffset); |
| 151 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 152 | // These values are per-channel of the input. |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 153 | auto mean = QuantizedVector<T>({ 3, -2 }, qScale, qOffset); |
| 154 | auto variance = QuantizedVector<T>({ 4, 9 }, qScale, qOffset); |
| 155 | auto beta = QuantizedVector<T>({ 3, 2 }, qScale, qOffset); |
| 156 | auto gamma = QuantizedVector<T>({ 2, 1 }, qScale, qOffset); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 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; |
James Conroy | 1f58f03 | 2021-04-27 17:13:27 +0100 | [diff] [blame] | 163 | armnn::ScopedTensorHandle meanTensor(tensorInfo); |
| 164 | armnn::ScopedTensorHandle varianceTensor(tensorInfo); |
| 165 | armnn::ScopedTensorHandle betaTensor(tensorInfo); |
| 166 | armnn::ScopedTensorHandle gammaTensor(tensorInfo); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 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 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 182 | std::vector<T> actualOutput(outputTensorInfo.GetNumElements()); |
| 183 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 184 | // For each channel: |
| 185 | // substract mean, divide by standard deviation (with an epsilon to avoid div by 0), |
| 186 | // multiply by gamma and add beta |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 187 | std::vector<T> expectedOutput = QuantizedVector<T>( |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 188 | { |
| 189 | 1.f, 3.f, 4.f, 3.f, |
| 190 | 4.f, 4.f, 2.f, 3.f, |
| 191 | 1.f, 2.f, 6.f, 4.f |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 192 | }, |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 193 | qScale, qOffset); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 194 | |
| 195 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateBatchNormalization(data, info); |
| 196 | |
| 197 | inputHandle->Allocate(); |
| 198 | outputHandle->Allocate(); |
| 199 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 200 | CopyDataToITensorHandle(inputHandle.get(), input.data()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 201 | |
| 202 | workload->Execute(); |
| 203 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 204 | CopyDataFromITensorHandle(actualOutput.data(), outputHandle.get()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 205 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 206 | return LayerTestResult<T, 4>(actualOutput, |
| 207 | expectedOutput, |
| 208 | outputHandle->GetShape(), |
| 209 | outputTensorInfo.GetShape()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 210 | } |
| 211 | |
| 212 | } // anonymous namespace |
| 213 | |
Matthew Jackson | 9bff144 | 2019-09-12 09:08:23 +0100 | [diff] [blame] | 214 | LayerTestResult<float, 4> BatchNormFloat32Test( |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 215 | armnn::IWorkloadFactory& workloadFactory, |
Keith Davis | 33a626f | 2020-08-27 15:38:12 +0100 | [diff] [blame] | 216 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 217 | const armnn::ITensorHandleFactory& tensorHandleFactory) |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 218 | { |
| 219 | // BatchSize: 1 |
| 220 | // Channels: 2 |
| 221 | // Height: 3 |
| 222 | // Width: 2 |
| 223 | |
| 224 | const armnn::TensorShape inputOutputShape{ 1, 2, 3, 2 }; |
| 225 | std::vector<float> inputValues |
| 226 | { |
| 227 | // Batch 0, Channel 0, Height (3) x Width (2) |
| 228 | 1.f, 4.f, |
| 229 | 4.f, 2.f, |
| 230 | 1.f, 6.f, |
| 231 | |
| 232 | // Batch 0, Channel 1, Height (3) x Width (2) |
| 233 | 1.f, 1.f, |
| 234 | 4.f, 1.f, |
| 235 | -2.f, 4.f |
| 236 | }; |
| 237 | std::vector<float> expectedOutputValues |
| 238 | { |
| 239 | // Batch 0, Channel 0, Height (3) x Width (2) |
| 240 | 1.f, 4.f, |
| 241 | 4.f, 2.f, |
| 242 | 1.f, 6.f, |
| 243 | |
| 244 | // Batch 0, Channel 1, Height (3) x Width (2) |
| 245 | 3.f, 3.f, |
| 246 | 4.f, 3.f, |
| 247 | 2.f, 4.f |
| 248 | }; |
| 249 | |
| 250 | return BatchNormTestImpl<armnn::DataType::Float32>( |
| 251 | workloadFactory, |
| 252 | memoryManager, |
Keith Davis | 33a626f | 2020-08-27 15:38:12 +0100 | [diff] [blame] | 253 | tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 254 | inputOutputShape, |
| 255 | inputValues, |
| 256 | expectedOutputValues, |
| 257 | 0.f, |
| 258 | 0, |
| 259 | armnn::DataLayout::NCHW); |
| 260 | } |
| 261 | |
Matthew Jackson | 9bff144 | 2019-09-12 09:08:23 +0100 | [diff] [blame] | 262 | LayerTestResult<float, 4> BatchNormFloat32NhwcTest( |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 263 | armnn::IWorkloadFactory& workloadFactory, |
Keith Davis | 33a626f | 2020-08-27 15:38:12 +0100 | [diff] [blame] | 264 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 265 | const armnn::ITensorHandleFactory& tensorHandleFactory) |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 266 | { |
| 267 | // BatchSize: 1 |
| 268 | // Height: 3 |
| 269 | // Width: 2 |
| 270 | // Channels: 2 |
| 271 | |
| 272 | const armnn::TensorShape inputOutputShape{ 1, 3, 2, 2 }; |
| 273 | std::vector<float> inputValues |
| 274 | { |
| 275 | // Batch 0, Height 0, Width (2) x Channel (2) |
| 276 | 1.f, 1.f, |
| 277 | 4.f, 1.f, |
| 278 | |
| 279 | // Batch 0, Height 1, Width (2) x Channel (2) |
| 280 | 4.f, 4.f, |
| 281 | 2.f, 1.f, |
| 282 | |
| 283 | // Batch 0, Height 2, Width (2) x Channel (2) |
| 284 | 1.f, -2.f, |
| 285 | 6.f, 4.f |
| 286 | }; |
| 287 | std::vector<float> expectedOutputValues |
| 288 | { |
| 289 | // Batch 0, Height 0, Width (2) x Channel (2) |
| 290 | 1.f, 3.f, |
| 291 | 4.f, 3.f, |
| 292 | |
| 293 | // Batch 0, Height 1, Width (2) x Channel (2) |
| 294 | 4.f, 4.f, |
| 295 | 2.f, 3.f, |
| 296 | |
| 297 | // Batch 0, Height 2, Width (2) x Channel (2) |
| 298 | 1.f, 2.f, |
| 299 | 6.f, 4.f |
| 300 | }; |
| 301 | |
| 302 | return BatchNormTestImpl<armnn::DataType::Float32>( |
| 303 | workloadFactory, |
| 304 | memoryManager, |
Keith Davis | 33a626f | 2020-08-27 15:38:12 +0100 | [diff] [blame] | 305 | tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 306 | inputOutputShape, |
| 307 | inputValues, |
| 308 | expectedOutputValues, |
| 309 | 0.f, |
| 310 | 0, |
| 311 | armnn::DataLayout::NHWC); |
| 312 | } |
| 313 | |
Matthew Jackson | 9bff144 | 2019-09-12 09:08:23 +0100 | [diff] [blame] | 314 | LayerTestResult<armnn::Half, 4> BatchNormFloat16Test( |
| 315 | armnn::IWorkloadFactory& workloadFactory, |
Keith Davis | 33a626f | 2020-08-27 15:38:12 +0100 | [diff] [blame] | 316 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 317 | const armnn::ITensorHandleFactory& tensorHandleFactory) |
Matthew Jackson | 9bff144 | 2019-09-12 09:08:23 +0100 | [diff] [blame] | 318 | { |
| 319 | // BatchSize: 1 |
| 320 | // Channels: 2 |
| 321 | // Height: 3 |
| 322 | // Width: 2 |
| 323 | |
| 324 | const armnn::TensorShape inputOutputShape{ 1, 2, 3, 2 }; |
| 325 | std::vector<float> inputValues |
| 326 | { |
| 327 | // Batch 0, Channel 0, Height (3) x Width (2) |
| 328 | 1.f, 4.f, |
| 329 | 4.f, 2.f, |
| 330 | 1.f, 6.f, |
| 331 | |
| 332 | // Batch 0, Channel 1, Height (3) x Width (2) |
| 333 | 1.f, 1.f, |
| 334 | 4.f, 1.f, |
| 335 | -2.f, 4.f |
| 336 | }; |
| 337 | std::vector<float> expectedOutputValues |
| 338 | { |
| 339 | // Batch 0, Channel 0, Height (3) x Width (2) |
| 340 | 1.f, 4.f, |
| 341 | 4.f, 2.f, |
| 342 | 1.f, 6.f, |
| 343 | |
| 344 | // Batch 0, Channel 1, Height (3) x Width (2) |
| 345 | 3.f, 3.f, |
| 346 | 4.f, 3.f, |
| 347 | 2.f, 4.f |
| 348 | }; |
| 349 | |
| 350 | return BatchNormTestImpl<armnn::DataType::Float16>( |
| 351 | workloadFactory, |
| 352 | memoryManager, |
Keith Davis | 33a626f | 2020-08-27 15:38:12 +0100 | [diff] [blame] | 353 | tensorHandleFactory, |
Matthew Jackson | 9bff144 | 2019-09-12 09:08:23 +0100 | [diff] [blame] | 354 | inputOutputShape, |
| 355 | inputValues, |
| 356 | expectedOutputValues, |
| 357 | 0.f, |
| 358 | 0, |
| 359 | armnn::DataLayout::NCHW); |
| 360 | } |
| 361 | |
| 362 | LayerTestResult<armnn::Half, 4> BatchNormFloat16NhwcTest( |
| 363 | armnn::IWorkloadFactory& workloadFactory, |
Keith Davis | 33a626f | 2020-08-27 15:38:12 +0100 | [diff] [blame] | 364 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 365 | const armnn::ITensorHandleFactory& tensorHandleFactory) |
Matthew Jackson | 9bff144 | 2019-09-12 09:08:23 +0100 | [diff] [blame] | 366 | { |
| 367 | // BatchSize: 1 |
| 368 | // Height: 3 |
| 369 | // Width: 2 |
| 370 | // Channels: 2 |
| 371 | |
| 372 | const armnn::TensorShape inputOutputShape{ 1, 3, 2, 2 }; |
| 373 | std::vector<float> inputValues |
| 374 | { |
| 375 | // Batch 0, Height 0, Width (2) x Channel (2) |
| 376 | 1.f, 1.f, |
| 377 | 4.f, 1.f, |
| 378 | |
| 379 | // Batch 0, Height 1, Width (2) x Channel (2) |
| 380 | 4.f, 4.f, |
| 381 | 2.f, 1.f, |
| 382 | |
| 383 | // Batch 0, Height 2, Width (2) x Channel (2) |
| 384 | 1.f, -2.f, |
| 385 | 6.f, 4.f |
| 386 | }; |
| 387 | std::vector<float> expectedOutputValues |
| 388 | { |
| 389 | // Batch 0, Height 0, Width (2) x Channel (2) |
| 390 | 1.f, 3.f, |
| 391 | 4.f, 3.f, |
| 392 | |
| 393 | // Batch 0, Height 1, Width (2) x Channel (2) |
| 394 | 4.f, 4.f, |
| 395 | 2.f, 3.f, |
| 396 | |
| 397 | // Batch 0, Height 2, Width (2) x Channel (2) |
| 398 | 1.f, 2.f, |
| 399 | 6.f, 4.f |
| 400 | }; |
| 401 | |
| 402 | return BatchNormTestImpl<armnn::DataType::Float16>( |
| 403 | workloadFactory, |
| 404 | memoryManager, |
Keith Davis | 33a626f | 2020-08-27 15:38:12 +0100 | [diff] [blame] | 405 | tensorHandleFactory, |
Matthew Jackson | 9bff144 | 2019-09-12 09:08:23 +0100 | [diff] [blame] | 406 | inputOutputShape, |
| 407 | inputValues, |
| 408 | expectedOutputValues, |
| 409 | 0.f, |
| 410 | 0, |
| 411 | armnn::DataLayout::NHWC); |
| 412 | } |
| 413 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 414 | LayerTestResult<uint8_t, 4> BatchNormUint8Test( |
| 415 | armnn::IWorkloadFactory& workloadFactory, |
Keith Davis | 33a626f | 2020-08-27 15:38:12 +0100 | [diff] [blame] | 416 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 417 | const armnn::ITensorHandleFactory& tensorHandleFactory) |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 418 | { |
| 419 | // BatchSize: 1 |
| 420 | // Channels: 2 |
| 421 | // Height: 3 |
| 422 | // Width: 2 |
| 423 | |
| 424 | const armnn::TensorShape inputOutputShape{ 1, 2, 3, 2 }; |
| 425 | std::vector<float> inputValues |
| 426 | { |
| 427 | // Batch 0, Channel 0, Height (3) x Width (2) |
| 428 | 1.f, 4.f, |
| 429 | 4.f, 2.f, |
| 430 | 1.f, 6.f, |
| 431 | |
| 432 | // Batch 0, Channel 1, Height (3) x Width (2) |
| 433 | 1.f, 1.f, |
| 434 | 4.f, 1.f, |
| 435 | -2.f, 4.f |
| 436 | }; |
| 437 | std::vector<float> expectedOutputValues |
| 438 | { |
| 439 | // Batch 0, Channel 0, Height (3) x Width (2) |
| 440 | 1.f, 4.f, |
| 441 | 4.f, 2.f, |
| 442 | 1.f, 6.f, |
| 443 | |
| 444 | // Batch 0, Channel 1, Height (3) x Width (2) |
| 445 | 3.f, 3.f, |
| 446 | 4.f, 3.f, |
| 447 | 2.f, 4.f |
| 448 | }; |
| 449 | |
Derek Lamberti | f90c56d | 2020-01-10 17:14:08 +0000 | [diff] [blame] | 450 | return BatchNormTestImpl<armnn::DataType::QAsymmU8>( |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 451 | workloadFactory, |
| 452 | memoryManager, |
Keith Davis | 33a626f | 2020-08-27 15:38:12 +0100 | [diff] [blame] | 453 | tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 454 | inputOutputShape, |
| 455 | inputValues, |
| 456 | expectedOutputValues, |
| 457 | 1.f / 20.f, |
| 458 | 50, |
| 459 | armnn::DataLayout::NCHW); |
| 460 | } |
| 461 | |
| 462 | LayerTestResult<uint8_t, 4> BatchNormUint8NhwcTest( |
| 463 | armnn::IWorkloadFactory& workloadFactory, |
Keith Davis | 33a626f | 2020-08-27 15:38:12 +0100 | [diff] [blame] | 464 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 465 | const armnn::ITensorHandleFactory& tensorHandleFactory) |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 466 | { |
| 467 | // BatchSize: 1 |
| 468 | // Height: 3 |
| 469 | // Width: 2 |
| 470 | // Channels: 2 |
| 471 | |
| 472 | const armnn::TensorShape inputOutputShape{ 1, 3, 2, 2 }; |
| 473 | std::vector<float> inputValues |
| 474 | { |
| 475 | // Batch 0, Height 0, Width (2) x Channel (2) |
| 476 | 1.f, 1.f, |
| 477 | 4.f, 1.f, |
| 478 | |
| 479 | // Batch 0, Height 1, Width (2) x Channel (2) |
| 480 | 4.f, 4.f, |
| 481 | 2.f, 1.f, |
| 482 | |
| 483 | // Batch 0, Height 2, Width (2) x Channel (2) |
| 484 | 1.f, -2.f, |
| 485 | 6.f, 4.f |
| 486 | }; |
| 487 | std::vector<float> expectedOutputValues |
| 488 | { |
| 489 | // Batch 0, Height 0, Width (2) x Channel (2) |
| 490 | 1.f, 3.f, |
| 491 | 4.f, 3.f, |
| 492 | |
| 493 | // Batch 0, Height 1, Width (2) x Channel (2) |
| 494 | 4.f, 4.f, |
| 495 | 2.f, 3.f, |
| 496 | |
| 497 | // Batch 0, Height 2, Width (2) x Channel (2) |
| 498 | 1.f, 2.f, |
| 499 | 6.f, 4.f |
| 500 | }; |
| 501 | |
Derek Lamberti | f90c56d | 2020-01-10 17:14:08 +0000 | [diff] [blame] | 502 | return BatchNormTestImpl<armnn::DataType::QAsymmU8>( |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 503 | workloadFactory, |
| 504 | memoryManager, |
Keith Davis | 33a626f | 2020-08-27 15:38:12 +0100 | [diff] [blame] | 505 | tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 506 | inputOutputShape, inputValues, expectedOutputValues, |
| 507 | 1.f/20.f, 50, armnn::DataLayout::NHWC); |
| 508 | } |
| 509 | |
| 510 | LayerTestResult<int16_t, 4> BatchNormInt16Test( |
| 511 | armnn::IWorkloadFactory& workloadFactory, |
Keith Davis | 33a626f | 2020-08-27 15:38:12 +0100 | [diff] [blame] | 512 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 513 | const armnn::ITensorHandleFactory& tensorHandleFactory) |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 514 | { |
| 515 | // BatchSize: 1 |
| 516 | // Channels: 2 |
| 517 | // Height: 3 |
| 518 | // Width: 2 |
| 519 | |
| 520 | const armnn::TensorShape inputOutputShape{ 1, 2, 3, 2 }; |
| 521 | std::vector<float> inputValues |
| 522 | { |
| 523 | // Batch 0, Channel 0, Height (3) x Width (2) |
| 524 | 1.f, 4.f, |
| 525 | 4.f, 2.f, |
| 526 | 1.f, 6.f, |
| 527 | |
| 528 | // Batch 0, Channel 1, Height (3) x Width (2) |
| 529 | 1.f, 1.f, |
| 530 | 4.f, 1.f, |
| 531 | -2.f, 4.f |
| 532 | }; |
| 533 | std::vector<float> expectedOutputValues |
| 534 | { |
| 535 | // Batch 0, Channel 0, Height (3) x Width (2) |
| 536 | 1.f, 4.f, |
| 537 | 4.f, 2.f, |
| 538 | 1.f, 6.f, |
| 539 | |
| 540 | // Batch 0, Channel 1, Height (3) x Width (2) |
| 541 | 3.f, 3.f, |
| 542 | 4.f, 3.f, |
| 543 | 2.f, 4.f |
| 544 | }; |
| 545 | |
Derek Lamberti | f90c56d | 2020-01-10 17:14:08 +0000 | [diff] [blame] | 546 | return BatchNormTestImpl<armnn::DataType::QSymmS16>( |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 547 | workloadFactory, |
| 548 | memoryManager, |
Keith Davis | 33a626f | 2020-08-27 15:38:12 +0100 | [diff] [blame] | 549 | tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 550 | inputOutputShape, |
| 551 | inputValues, |
| 552 | expectedOutputValues, |
| 553 | 1.f / 20.f, |
| 554 | 50, |
| 555 | armnn::DataLayout::NCHW); |
| 556 | } |
| 557 | |
| 558 | LayerTestResult<int16_t, 4> BatchNormInt16NhwcTest( |
| 559 | armnn::IWorkloadFactory& workloadFactory, |
Keith Davis | 33a626f | 2020-08-27 15:38:12 +0100 | [diff] [blame] | 560 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 561 | const armnn::ITensorHandleFactory& tensorHandleFactory) |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 562 | { |
| 563 | // BatchSize: 1 |
| 564 | // Height: 3 |
| 565 | // Width: 2 |
| 566 | // Channels: 2 |
| 567 | |
| 568 | const armnn::TensorShape inputOutputShape{ 1, 3, 2, 2 }; |
| 569 | std::vector<float> inputValues |
| 570 | { |
| 571 | // Batch 0, Height 0, Width (2) x Channel (2) |
| 572 | 1.f, 1.f, |
| 573 | 4.f, 1.f, |
| 574 | |
| 575 | // Batch 0, Height 1, Width (2) x Channel (2) |
| 576 | 4.f, 4.f, |
| 577 | 2.f, 1.f, |
| 578 | |
| 579 | // Batch 0, Height 2, Width (2) x Channel (2) |
| 580 | 1.f, -2.f, |
| 581 | 6.f, 4.f |
| 582 | }; |
| 583 | std::vector<float> expectedOutputValues |
| 584 | { |
| 585 | // Batch 0, Height 0, Width (2) x Channel (2) |
| 586 | 1.f, 3.f, |
| 587 | 4.f, 3.f, |
| 588 | |
| 589 | // Batch 0, Height 1, Width (2) x Channel (2) |
| 590 | 4.f, 4.f, |
| 591 | 2.f, 3.f, |
| 592 | |
| 593 | // Batch 0, Height 2, Width (2) x Channel (2) |
| 594 | 1.f, 2.f, |
| 595 | 6.f, 4.f |
| 596 | }; |
| 597 | |
Derek Lamberti | f90c56d | 2020-01-10 17:14:08 +0000 | [diff] [blame] | 598 | return BatchNormTestImpl<armnn::DataType::QSymmS16>( |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 599 | workloadFactory, |
| 600 | memoryManager, |
Keith Davis | 33a626f | 2020-08-27 15:38:12 +0100 | [diff] [blame] | 601 | tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 602 | inputOutputShape, |
| 603 | inputValues, |
| 604 | expectedOutputValues, |
| 605 | 1.f / 20.f, |
| 606 | 50, |
| 607 | armnn::DataLayout::NHWC); |
| 608 | } |
| 609 | |
| 610 | LayerTestResult<float,4> CompareBatchNormTest( |
| 611 | armnn::IWorkloadFactory& workloadFactory, |
| 612 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | 33a626f | 2020-08-27 15:38:12 +0100 | [diff] [blame] | 613 | armnn::IWorkloadFactory& refWorkloadFactory, |
| 614 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
| 615 | const armnn::ITensorHandleFactory& refTensorHandleFactory) |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 616 | { |
Jan Eilers | 8eb2560 | 2020-03-09 12:13:48 +0000 | [diff] [blame] | 617 | IgnoreUnused(memoryManager); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 618 | const unsigned int width = 2; |
| 619 | const unsigned int height = 3; |
| 620 | const unsigned int channels = 5; |
| 621 | const unsigned int batchSize = 3; |
| 622 | |
| 623 | armnn::TensorInfo inputTensorInfo; |
| 624 | armnn::TensorInfo outputTensorInfo; |
| 625 | armnn::TensorInfo tensorInfo; |
| 626 | |
| 627 | constexpr unsigned int shape[] = {batchSize, channels, height, width}; |
| 628 | constexpr unsigned int tensorShape[] = {channels}; |
| 629 | |
| 630 | inputTensorInfo = armnn::TensorInfo(4, shape, armnn::DataType::Float32); |
| 631 | outputTensorInfo = armnn::TensorInfo(4, shape, armnn::DataType::Float32); |
| 632 | tensorInfo = armnn::TensorInfo(1, tensorShape, armnn::DataType::Float32); |
| 633 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 634 | auto input = MakeRandomTensor<float>(inputTensorInfo, 21312); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 635 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 636 | auto mean = MakeRandomTensor<float>(tensorInfo, 123); |
| 637 | auto variance = MakeRandomTensor<float>(tensorInfo, 234, 0.0f); |
| 638 | auto beta = MakeRandomTensor<float>(tensorInfo, 123); |
| 639 | auto gamma = MakeRandomTensor<float>(tensorInfo, 345); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 640 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 641 | std::vector<float> actualOutput(outputTensorInfo.GetNumElements()); |
| 642 | std::vector<float> expectedOutput(outputTensorInfo.GetNumElements()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 643 | |
Keith Davis | 33a626f | 2020-08-27 15:38:12 +0100 | [diff] [blame] | 644 | std::unique_ptr<armnn::ITensorHandle> inputHandle = tensorHandleFactory.CreateTensorHandle(inputTensorInfo); |
| 645 | std::unique_ptr<armnn::ITensorHandle> outputHandle = tensorHandleFactory.CreateTensorHandle(outputTensorInfo); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 646 | |
Keith Davis | 33a626f | 2020-08-27 15:38:12 +0100 | [diff] [blame] | 647 | std::unique_ptr<armnn::ITensorHandle> inputHandleRef = refTensorHandleFactory.CreateTensorHandle(inputTensorInfo); |
| 648 | std::unique_ptr<armnn::ITensorHandle> outputHandleRef = refTensorHandleFactory.CreateTensorHandle(outputTensorInfo); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 649 | |
| 650 | armnn::BatchNormalizationQueueDescriptor data; |
| 651 | armnn::WorkloadInfo info; |
James Conroy | 1f58f03 | 2021-04-27 17:13:27 +0100 | [diff] [blame] | 652 | armnn::ScopedTensorHandle meanTensor(tensorInfo); |
| 653 | armnn::ScopedTensorHandle varianceTensor(tensorInfo); |
| 654 | armnn::ScopedTensorHandle betaTensor(tensorInfo); |
| 655 | armnn::ScopedTensorHandle gammaTensor(tensorInfo); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 656 | |
| 657 | AllocateAndCopyDataToITensorHandle(&meanTensor, &mean[0]); |
| 658 | AllocateAndCopyDataToITensorHandle(&varianceTensor, &variance[0]); |
| 659 | AllocateAndCopyDataToITensorHandle(&betaTensor, &beta[0]); |
| 660 | AllocateAndCopyDataToITensorHandle(&gammaTensor, &gamma[0]); |
| 661 | |
| 662 | AddInputToWorkload(data, info, inputTensorInfo, inputHandle.get()); |
| 663 | AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get()); |
| 664 | data.m_Mean = &meanTensor; |
| 665 | data.m_Variance = &varianceTensor; |
| 666 | data.m_Beta = &betaTensor; |
| 667 | data.m_Gamma = &gammaTensor; |
| 668 | data.m_Parameters.m_Eps = 0.01f; |
| 669 | |
| 670 | armnn::BatchNormalizationQueueDescriptor refData = data; |
| 671 | armnn::WorkloadInfo refInfo = info; |
| 672 | SetWorkloadInput(refData, refInfo, 0, inputTensorInfo, inputHandleRef.get()); |
| 673 | SetWorkloadOutput(refData, refInfo, 0, outputTensorInfo, outputHandleRef.get()); |
| 674 | |
| 675 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateBatchNormalization(data, info); |
| 676 | std::unique_ptr<armnn::IWorkload> workloadRef = refWorkloadFactory.CreateBatchNormalization(refData, refInfo); |
| 677 | |
| 678 | inputHandle->Allocate(); |
| 679 | outputHandle->Allocate(); |
| 680 | inputHandleRef->Allocate(); |
| 681 | outputHandleRef->Allocate(); |
| 682 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 683 | CopyDataToITensorHandle(inputHandle.get(), input.data()); |
| 684 | CopyDataToITensorHandle(inputHandleRef.get(), input.data()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 685 | |
| 686 | workload->PostAllocationConfigure(); |
| 687 | workload->Execute(); |
| 688 | workloadRef->PostAllocationConfigure(); |
| 689 | workloadRef->Execute(); |
| 690 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 691 | CopyDataFromITensorHandle(actualOutput.data(), outputHandle.get()); |
| 692 | CopyDataFromITensorHandle(expectedOutput.data(), outputHandleRef.get()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 693 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 694 | return LayerTestResult<float, 4>(actualOutput, |
| 695 | expectedOutput, |
| 696 | outputHandle->GetShape(), |
| 697 | outputTensorInfo.GetShape()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 698 | } |