telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1 | // |
| 2 | // Copyright © 2017 Arm Ltd. All rights reserved. |
David Beck | ecb56cd | 2018-09-05 12:52:57 +0100 | [diff] [blame] | 3 | // SPDX-License-Identifier: MIT |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 4 | // |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 6 | #include "ActivationTestImpl.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> |
Aron Virginas-Tar | c9cc804 | 2018-11-01 16:15:57 +0000 | [diff] [blame] | 10 | |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 11 | #include <armnn/ArmNN.hpp> |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 12 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 13 | #include <backendsCommon/test/ActivationFixture.hpp> |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 14 | #include <backendsCommon/test/TensorCopyUtils.hpp> |
| 15 | #include <backendsCommon/test/WorkloadTestUtils.hpp> |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 16 | |
Aron Virginas-Tar | c9cc804 | 2018-11-01 16:15:57 +0000 | [diff] [blame] | 17 | #include <test/TensorHelpers.hpp> |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 18 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 19 | #include <boost/multi_array.hpp> |
| 20 | |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 21 | #include <algorithm> |
| 22 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 23 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 24 | LayerTestResult<T, 4> BoundedReLuTestCommon( |
| 25 | armnn::IWorkloadFactory& workloadFactory, |
| 26 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 27 | float upperBound, |
| 28 | float lowerBound, |
| 29 | float inputScale, |
| 30 | int32_t inputOffset, |
| 31 | float outputScale, |
| 32 | int32_t outputOffset, |
| 33 | const std::vector<T>& inputData, |
| 34 | const std::vector<T>& outputExpectedData, |
| 35 | unsigned int inputWidth, |
| 36 | unsigned int inputHeight, |
| 37 | unsigned int inputChannels, |
| 38 | unsigned int inputBatchSize) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 39 | { |
| 40 | unsigned int outputWidth = inputWidth; |
| 41 | unsigned int outputHeight = inputHeight; |
| 42 | unsigned int outputChannels = inputChannels; |
| 43 | unsigned int outputBatchSize = inputBatchSize; |
| 44 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 45 | armnn::TensorInfo inputTensorInfo({ inputBatchSize, inputChannels, inputHeight, inputWidth }, ArmnnType); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 46 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 47 | armnn::TensorInfo outputTensorInfo({ outputBatchSize, outputChannels, outputHeight, outputWidth }, ArmnnType); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 48 | |
| 49 | if(armnn::IsQuantizedType<T>()) |
| 50 | { |
| 51 | inputTensorInfo.SetQuantizationScale(inputScale); |
| 52 | inputTensorInfo.SetQuantizationOffset(inputOffset); |
| 53 | |
| 54 | outputTensorInfo.SetQuantizationScale(outputScale); |
| 55 | outputTensorInfo.SetQuantizationOffset(outputOffset); |
| 56 | } |
| 57 | |
| 58 | LayerTestResult<T, 4> result(inputTensorInfo); |
| 59 | |
| 60 | auto input = MakeTensor<T, 4>(inputTensorInfo, inputData); |
| 61 | |
| 62 | std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo); |
| 63 | std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); |
| 64 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 65 | // Setup bounded ReLu. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 66 | armnn::ActivationQueueDescriptor descriptor; |
| 67 | armnn::WorkloadInfo workloadInfo; |
| 68 | AddInputToWorkload(descriptor, workloadInfo, inputTensorInfo, inputHandle.get()); |
| 69 | AddOutputToWorkload(descriptor, workloadInfo, outputTensorInfo, outputHandle.get()); |
| 70 | |
| 71 | descriptor.m_Parameters.m_Function = armnn::ActivationFunction::BoundedReLu; |
| 72 | descriptor.m_Parameters.m_A = upperBound; |
| 73 | descriptor.m_Parameters.m_B = lowerBound; |
| 74 | |
| 75 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateActivation(descriptor, workloadInfo); |
| 76 | |
| 77 | inputHandle->Allocate(); |
| 78 | outputHandle->Allocate(); |
| 79 | |
| 80 | CopyDataToITensorHandle(inputHandle.get(), &input[0][0][0][0]); |
| 81 | |
| 82 | workload->Execute(); |
| 83 | |
| 84 | CopyDataFromITensorHandle(&result.output[0][0][0][0], outputHandle.get()); |
| 85 | |
| 86 | result.outputExpected = MakeTensor<T, 4>(outputTensorInfo, outputExpectedData); |
| 87 | |
| 88 | return result; |
| 89 | } |
| 90 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 91 | LayerTestResult<float, 4> BoundedReLuUpperAndLowerBoundTest( |
| 92 | armnn::IWorkloadFactory& workloadFactory, |
| 93 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 94 | { |
| 95 | unsigned int inputWidth = 4u; |
| 96 | unsigned int inputHeight = 5u; |
| 97 | unsigned int inputChannels = 1u; |
| 98 | unsigned int inputBatchSize = 1; |
| 99 | |
| 100 | std::vector<float> input = std::vector<float>{ |
| 101 | -2.0f, 0.1f, 0.5f, 1.25f, |
| 102 | 0.786f, 0.9875f, -1.5f, 0.384f, |
| 103 | 1.0001f, 3.5f, 7.5f, 0.896f, |
| 104 | 2.126f, 2.0f, 0.3f, 0.15f, |
| 105 | 0.999f, 1.2f, 0.89f, 6.1f, |
| 106 | }; |
| 107 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 108 | // Calculated manually. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 109 | std::vector<float> output = std::vector<float>{ |
| 110 | -1.0f, 0.1f, 0.5f, 1.0f, |
| 111 | 0.786f, 0.9875f, -1.0f, 0.384f, |
| 112 | 1.0f, 1.0f, 1.0f, 0.896f, |
| 113 | 1.0f, 1.0f, 0.3f, 0.15f, |
| 114 | 0.999f, 1.0f, 0.89f, 1.0f, |
| 115 | }; |
| 116 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 117 | return BoundedReLuTestCommon<armnn::DataType::Float32>( |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 118 | workloadFactory, memoryManager, 1.0f, -1.0f, 1.0f, 0, 1.0f, 0, input, output, |
| 119 | inputWidth, inputHeight, inputChannels, inputBatchSize); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 120 | } |
| 121 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 122 | LayerTestResult<float, 4> BoundedReLuUpperBoundOnlyTest( |
| 123 | armnn::IWorkloadFactory& workloadFactory, |
| 124 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 125 | { |
| 126 | unsigned int inputWidth = 4u; |
| 127 | unsigned int inputHeight = 5u; |
| 128 | unsigned int inputChannels = 1u; |
| 129 | unsigned int inputBatchSize = 1; |
| 130 | |
| 131 | std::vector<float> input = std::vector<float>{ |
| 132 | -1.0f, 0.1f, 0.5f, 6.25f, |
| 133 | 0.786f, 5.9875f, -0.5f, 0.384f, |
| 134 | 6.0001f, 3.5f, 7.5f, 0.896f, |
| 135 | 2.126f, 12.0f, 0.3f, 0.15f, |
| 136 | 0.999f, 1.2f, 0.89f, 6.1f, |
| 137 | }; |
| 138 | |
David Beck | ac42efd | 2018-09-26 17:41:13 +0100 | [diff] [blame] | 139 | // Calculated manually. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 140 | std::vector<float> output = std::vector<float>{ |
| 141 | 0.0f, 0.1f, 0.5f, 6.0f, |
| 142 | 0.786f, 5.9875f, 0.0f, 0.384f, |
| 143 | 6.0f, 3.5f, 6.0f, 0.896f, |
| 144 | 2.126f, 6.0f, 0.3f, 0.15f, |
| 145 | 0.999f, 1.2f, 0.89f, 6.0f, |
| 146 | }; |
| 147 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 148 | return BoundedReLuTestCommon<armnn::DataType::Float32>( |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 149 | workloadFactory, memoryManager, 6.0f, 0.0f, 1.0f, 0, 1.0f, 0, input, output, |
| 150 | inputWidth, inputHeight, inputChannels, inputBatchSize); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 151 | } |
| 152 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 153 | LayerTestResult<uint8_t, 4> BoundedReLuUint8UpperBoundOnlyTest( |
| 154 | armnn::IWorkloadFactory& workloadFactory, |
| 155 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 156 | { |
| 157 | unsigned int inputWidth = 3u; |
| 158 | unsigned int inputHeight = 2u; |
| 159 | unsigned int inputChannels = 1u; |
| 160 | unsigned int inputBatchSize = 1; |
| 161 | |
| 162 | std::vector<uint8_t> input = std::vector<uint8_t>{ |
| 163 | 51, 124, 28, |
| 164 | 251, 8, 92 |
| 165 | }; |
| 166 | |
David Beck | ac42efd | 2018-09-26 17:41:13 +0100 | [diff] [blame] | 167 | // Calculated manually. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 168 | std::vector<uint8_t> output = std::vector<uint8_t>{ |
| 169 | 0, 122, 0, |
| 170 | 255, 0, 58 |
| 171 | }; |
| 172 | |
| 173 | float inputScale = 12.0f / 255.0f; |
| 174 | int32_t inputOffset = 63; |
| 175 | float outputScale = 6.0f / 255.0f; |
| 176 | int32_t outputOffset = 0; |
| 177 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 178 | return BoundedReLuTestCommon<armnn::DataType::QuantisedAsymm8>( |
| 179 | workloadFactory, memoryManager, 6.0f, 0.0f, |
| 180 | inputScale, inputOffset, outputScale, outputOffset, |
| 181 | input, output, inputWidth, inputHeight, inputChannels, inputBatchSize); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 182 | } |
| 183 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 184 | LayerTestResult<uint8_t, 4> BoundedReLuUint8UpperAndLowerBoundTest( |
| 185 | armnn::IWorkloadFactory& workloadFactory, |
| 186 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 187 | { |
| 188 | unsigned int inputWidth = 3u; |
| 189 | unsigned int inputHeight = 2u; |
| 190 | unsigned int inputChannels = 1u; |
| 191 | unsigned int inputBatchSize = 1; |
| 192 | |
| 193 | std::vector<uint8_t> input = std::vector<uint8_t>{ |
| 194 | 51, 230, 28, |
| 195 | 251, 8, 92 |
| 196 | }; |
| 197 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 198 | // Calculated manually. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 199 | std::vector<uint8_t> output = std::vector<uint8_t>{ |
| 200 | 51, 192, 32, |
| 201 | 192, 32, 92 |
| 202 | }; |
| 203 | |
| 204 | int32_t inputOffset = 112; |
| 205 | float inputScale = 0.0125f; |
| 206 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 207 | return BoundedReLuTestCommon<armnn::DataType::QuantisedAsymm8>( |
| 208 | workloadFactory, memoryManager, 1.0f, -1.0f, |
| 209 | inputScale, inputOffset, inputScale, inputOffset, // Input/output scale & offset same. |
| 210 | input, output, inputWidth, inputHeight, inputChannels, inputBatchSize); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 211 | } |
| 212 | |
| 213 | namespace |
| 214 | { |
| 215 | |
| 216 | struct BoundedReLuRandomInputTestTraits |
| 217 | { |
| 218 | constexpr static unsigned int inputHeight = 31u; |
| 219 | constexpr static unsigned int inputWidth = 19u; |
| 220 | constexpr static unsigned int inputChannels = 4u; |
| 221 | constexpr static unsigned int inputBatchSize = 2; |
| 222 | |
| 223 | constexpr static unsigned int outputHeight = inputHeight; |
| 224 | constexpr static unsigned int outputWidth = inputWidth; |
| 225 | constexpr static unsigned int outputChannels = inputChannels; |
| 226 | constexpr static unsigned int outputBatchSize = inputBatchSize; |
| 227 | |
| 228 | static armnn::TensorInfo GetInputTensorInfo() |
| 229 | { |
| 230 | return armnn::TensorInfo({ inputBatchSize, inputChannels, inputHeight, inputWidth }, |
| 231 | armnn::DataType::Float32); |
| 232 | } |
| 233 | |
| 234 | static armnn::TensorInfo GetOutputTensorInfo() |
| 235 | { |
| 236 | return armnn::TensorInfo({ outputBatchSize, outputChannels, outputHeight, outputWidth }, |
| 237 | armnn::DataType::Float32); |
| 238 | } |
| 239 | }; |
| 240 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 241 | boost::multi_array<float, 4> BoundedReLuRandomInputTest( |
| 242 | armnn::IWorkloadFactory& workloadFactory, |
| 243 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 244 | float lowerBound, |
| 245 | float upperBound, |
| 246 | const armnn::ActivationDescriptor& activationDescriptor) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 247 | { |
| 248 | const armnn::TensorInfo inputTensorInfo = BoundedReLuRandomInputTestTraits::GetInputTensorInfo(); |
| 249 | const armnn::TensorInfo outputTensorInfo = BoundedReLuRandomInputTestTraits::GetOutputTensorInfo(); |
| 250 | |
| 251 | boost::multi_array<float, 4> output(GetTensorShapeAsArray<4>(outputTensorInfo)); |
| 252 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 253 | // Min/max random values passed to MakeRandomTensor are purposely outside of the ReLu |
| 254 | // range [lowerBound, upperBound]. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 255 | auto input = MakeRandomTensor<float, 4>(inputTensorInfo, 4605828, lowerBound - 5.0f, upperBound * 2.0f); |
| 256 | |
| 257 | std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo); |
| 258 | std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); |
| 259 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 260 | // Set up bounded ReLu. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 261 | armnn::ActivationQueueDescriptor descriptor; |
| 262 | armnn::WorkloadInfo workloadInfo; |
| 263 | AddInputToWorkload(descriptor, workloadInfo, inputTensorInfo, inputHandle.get()); |
| 264 | AddOutputToWorkload(descriptor, workloadInfo, outputTensorInfo, outputHandle.get()); |
| 265 | descriptor.m_Parameters = activationDescriptor; |
| 266 | |
| 267 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateActivation(descriptor, workloadInfo); |
| 268 | |
| 269 | inputHandle->Allocate(); |
| 270 | outputHandle->Allocate(); |
| 271 | |
| 272 | CopyDataToITensorHandle(inputHandle.get(), &input[0][0][0][0]); |
| 273 | |
| 274 | workload->Execute(); |
| 275 | |
| 276 | CopyDataFromITensorHandle(&output[0][0][0][0], outputHandle.get()); |
| 277 | |
| 278 | return output; |
| 279 | } |
| 280 | |
| 281 | } // namespace |
| 282 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 283 | LayerTestResult<float, 4> CompareBoundedReLuTest( |
| 284 | armnn::IWorkloadFactory& workloadFactory, |
| 285 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 286 | armnn::IWorkloadFactory& refWorkloadFactory, |
| 287 | float upperBound, |
| 288 | float lowerBound) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 289 | { |
| 290 | LayerTestResult<float, 4> result(BoundedReLuRandomInputTestTraits::GetOutputTensorInfo()); |
| 291 | |
| 292 | armnn::ActivationDescriptor activationDescriptor; |
| 293 | activationDescriptor.m_Function = armnn::ActivationFunction::BoundedReLu; |
| 294 | activationDescriptor.m_A = upperBound; |
| 295 | activationDescriptor.m_B = lowerBound; |
| 296 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 297 | result.output = BoundedReLuRandomInputTest( |
| 298 | workloadFactory, memoryManager, 0.0f, upperBound, activationDescriptor); |
| 299 | result.outputExpected = BoundedReLuRandomInputTest( |
| 300 | refWorkloadFactory, nullptr, 0.0f, upperBound, activationDescriptor); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 301 | |
| 302 | return result; |
| 303 | } |
| 304 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 305 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 306 | LayerTestResult<T,4> ConstantLinearActivationTestCommon( |
| 307 | armnn::IWorkloadFactory& workloadFactory, |
| 308 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 309 | float qScale = 0.0f, |
| 310 | int32_t qOffset = 0) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 311 | { |
| 312 | unsigned int inputHeight = 20; |
| 313 | unsigned int inputWidth = 17; |
| 314 | unsigned int inputChannels = 3; |
| 315 | unsigned int batchSize = 5; |
| 316 | |
| 317 | armnn::TensorInfo inputTensorInfo; |
| 318 | armnn::TensorInfo outputTensorInfo; |
| 319 | |
| 320 | unsigned int shape[] = {batchSize, inputChannels, inputHeight, inputWidth}; |
| 321 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 322 | inputTensorInfo = armnn::TensorInfo(4, shape, ArmnnType); |
| 323 | outputTensorInfo = armnn::TensorInfo(4, shape, ArmnnType); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 324 | |
| 325 | // Set quantization parameters if the requested type is a quantized type. |
| 326 | if(armnn::IsQuantizedType<T>()) |
| 327 | { |
| 328 | inputTensorInfo.SetQuantizationScale(qScale); |
| 329 | inputTensorInfo.SetQuantizationOffset(qOffset); |
| 330 | outputTensorInfo.SetQuantizationScale(qScale); |
| 331 | outputTensorInfo.SetQuantizationOffset(qOffset); |
| 332 | } |
| 333 | |
| 334 | LayerTestResult<T, 4> ret(outputTensorInfo); |
| 335 | |
| 336 | std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo); |
| 337 | std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); |
| 338 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 339 | // Do linear activation that should leave the tensor unchanged. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 340 | armnn::ActivationQueueDescriptor data; |
| 341 | armnn::WorkloadInfo info; |
| 342 | AddInputToWorkload(data, info, inputTensorInfo, inputHandle.get()); |
| 343 | AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get()); |
| 344 | data.m_Parameters.m_A = 1.0f; |
| 345 | data.m_Parameters.m_B = 0.0f; |
| 346 | data.m_Parameters.m_Function = armnn::ActivationFunction::Linear; |
| 347 | |
| 348 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateActivation(data, info); |
| 349 | |
| 350 | inputHandle->Allocate(); |
| 351 | outputHandle->Allocate(); |
| 352 | |
| 353 | boost::multi_array<T, 4> input = MakeRandomTensor<T, 4>(inputTensorInfo, 7123561); |
| 354 | CopyDataToITensorHandle(inputHandle.get(), &input[0][0][0][0]); |
| 355 | |
| 356 | workload->Execute(); |
| 357 | |
| 358 | CopyDataFromITensorHandle(&ret.output[0][0][0][0], outputHandle.get()); |
| 359 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 360 | // Ensure output equals input. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 361 | ret.outputExpected = input; |
| 362 | |
| 363 | return ret; |
| 364 | } |
| 365 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 366 | LayerTestResult<float, 4> ConstantLinearActivationTest( |
| 367 | armnn::IWorkloadFactory& workloadFactory, |
| 368 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 369 | { |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 370 | return ConstantLinearActivationTestCommon<armnn::DataType::Float32>(workloadFactory, memoryManager); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 371 | } |
| 372 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 373 | LayerTestResult<uint8_t, 4> ConstantLinearActivationUint8Test( |
| 374 | armnn::IWorkloadFactory& workloadFactory, |
| 375 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 376 | { |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 377 | return ConstantLinearActivationTestCommon<armnn::DataType::QuantisedAsymm8>( |
| 378 | workloadFactory, memoryManager, 4.0f, 3); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 379 | } |
| 380 | |
Teresa Charlin | 18515e2 | 2019-04-24 10:17:46 +0100 | [diff] [blame] | 381 | LayerTestResult<int16_t, 4> ConstantLinearActivationInt16Test( |
| 382 | armnn::IWorkloadFactory& workloadFactory, |
| 383 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 384 | { |
| 385 | return ConstantLinearActivationTestCommon<armnn::DataType::QuantisedSymm16>( |
| 386 | workloadFactory, memoryManager, 0.1f, 0); |
| 387 | } |
| 388 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 389 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 390 | LayerTestResult<T, 4> SimpleActivationTest( |
| 391 | armnn::IWorkloadFactory& workloadFactory, |
| 392 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 393 | armnn::ActivationFunction activationFunction, |
| 394 | float activationParameterA, |
| 395 | float activationParameterB, |
Ferran Balaguer | b2b5a26 | 2019-06-24 12:43:38 +0100 | [diff] [blame] | 396 | float scale, |
| 397 | int32_t offset, |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 398 | const std::vector<float>& inputData, |
Ferran Balaguer | b2b5a26 | 2019-06-24 12:43:38 +0100 | [diff] [blame] | 399 | float outScale, |
| 400 | int32_t outOffset, |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 401 | const std::vector<float>& outputExpectedData) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 402 | { |
| 403 | constexpr static unsigned int inputWidth = 16u; |
| 404 | constexpr static unsigned int inputHeight = 1u; |
| 405 | constexpr static unsigned int inputChannels = 1u; |
| 406 | constexpr static unsigned int inputBatchSize = 1u; |
| 407 | |
| 408 | constexpr static unsigned int outputWidth = inputWidth; |
| 409 | constexpr static unsigned int outputHeight = inputHeight; |
| 410 | constexpr static unsigned int outputChannels = inputChannels; |
| 411 | constexpr static unsigned int outputBatchSize = inputBatchSize; |
| 412 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 413 | armnn::TensorInfo inputTensorInfo({ inputBatchSize, inputChannels, inputHeight, inputWidth }, ArmnnType); |
| 414 | armnn::TensorInfo outputTensorInfo({ outputBatchSize, outputChannels, outputHeight, outputWidth }, ArmnnType); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 415 | |
| 416 | // Set quantization parameters if the requested type is a quantized type. |
| 417 | if(armnn::IsQuantizedType<T>()) |
| 418 | { |
Ferran Balaguer | b2b5a26 | 2019-06-24 12:43:38 +0100 | [diff] [blame] | 419 | inputTensorInfo.SetQuantizationScale(scale); |
| 420 | inputTensorInfo.SetQuantizationOffset(offset); |
| 421 | outputTensorInfo.SetQuantizationScale(outScale); |
| 422 | outputTensorInfo.SetQuantizationOffset(outOffset); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 423 | } |
| 424 | |
| 425 | LayerTestResult<T, 4> result(inputTensorInfo); |
| 426 | |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 427 | auto input = MakeTensor<T, 4>(inputTensorInfo, armnnUtils::QuantizedVector<T>(inputData, scale, offset)); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 428 | |
| 429 | std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo); |
| 430 | std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); |
| 431 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 432 | // Setup bounded ReLu. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 433 | armnn::ActivationQueueDescriptor descriptor; |
| 434 | armnn::WorkloadInfo workloadInfo; |
| 435 | AddInputToWorkload(descriptor, workloadInfo, inputTensorInfo, inputHandle.get()); |
| 436 | AddOutputToWorkload(descriptor, workloadInfo, outputTensorInfo, outputHandle.get()); |
| 437 | |
| 438 | descriptor.m_Parameters.m_Function = activationFunction; |
| 439 | descriptor.m_Parameters.m_A = activationParameterA; |
| 440 | descriptor.m_Parameters.m_B = activationParameterB; |
| 441 | |
| 442 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateActivation(descriptor, workloadInfo); |
| 443 | |
| 444 | inputHandle->Allocate(); |
| 445 | outputHandle->Allocate(); |
| 446 | |
| 447 | CopyDataToITensorHandle(inputHandle.get(), &input[0][0][0][0]); |
| 448 | |
| 449 | workload->Execute(); |
| 450 | |
| 451 | CopyDataFromITensorHandle(&result.output[0][0][0][0], outputHandle.get()); |
| 452 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 453 | // Calculated manually. |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 454 | result.outputExpected = |
| 455 | MakeTensor<T, 4>(outputTensorInfo, armnnUtils::QuantizedVector<T>(outputExpectedData, outScale, outOffset)); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 456 | |
| 457 | return result; |
| 458 | } |
| 459 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 460 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 461 | LayerTestResult<T, 4> SimpleSigmoidTestCommon( |
| 462 | armnn::IWorkloadFactory& workloadFactory, |
| 463 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 464 | float qScale, |
| 465 | int32_t qOffset) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 466 | { |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 467 | std::vector<float> inputData = |
| 468 | { |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 469 | -0.1f, -0.2f, -0.3f, -0.4f, |
| 470 | 0.1f, 0.2f, 0.3f, 0.4f, |
| 471 | -1.0f, -2.0f, -3.0f, -4.0f, |
| 472 | 1.0f, 2.0f, 3.0f, 4.0f |
| 473 | }; |
| 474 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 475 | // Calculate output values for input. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 476 | auto f = [](float value) |
| 477 | { |
| 478 | return 1.0f / (1.0f + std::exp(-value)); |
| 479 | }; |
| 480 | std::vector<float> outputExpectedData(inputData.size()); |
| 481 | std::transform(inputData.begin(), inputData.end(), outputExpectedData.begin(), f); |
| 482 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 483 | return SimpleActivationTest<ArmnnType>(workloadFactory, |
| 484 | memoryManager, |
| 485 | armnn::ActivationFunction::Sigmoid, |
| 486 | 0.f, |
| 487 | 0.f, |
| 488 | qScale, |
| 489 | qOffset, |
| 490 | inputData, |
Ferran Balaguer | b2b5a26 | 2019-06-24 12:43:38 +0100 | [diff] [blame] | 491 | 1.f / 256.f, |
| 492 | 0, |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 493 | outputExpectedData); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 494 | } |
| 495 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 496 | LayerTestResult<float, 4> SimpleSigmoidTest( |
| 497 | armnn::IWorkloadFactory& workloadFactory, |
| 498 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 499 | { |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 500 | return SimpleSigmoidTestCommon<armnn::DataType::Float32>(workloadFactory, memoryManager, 0.0f, 0); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 501 | } |
| 502 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 503 | LayerTestResult<uint8_t, 4> SimpleSigmoidUint8Test( |
| 504 | armnn::IWorkloadFactory& workloadFactory, |
| 505 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 506 | { |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 507 | return SimpleSigmoidTestCommon<armnn::DataType::QuantisedAsymm8>(workloadFactory, memoryManager, 0.1f, 50); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 508 | } |
| 509 | |
Teresa Charlin | 18515e2 | 2019-04-24 10:17:46 +0100 | [diff] [blame] | 510 | LayerTestResult<int16_t, 4> SimpleSigmoidInt16Test( |
| 511 | armnn::IWorkloadFactory& workloadFactory, |
| 512 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 513 | { |
| 514 | return SimpleSigmoidTestCommon<armnn::DataType::QuantisedSymm16>(workloadFactory, memoryManager, 0.1f, 0); |
| 515 | } |
| 516 | |
| 517 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
| 518 | LayerTestResult<T, 4> ReLuTestCommon( |
| 519 | armnn::IWorkloadFactory& workloadFactory, |
| 520 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 521 | float qScale, |
| 522 | int32_t qOffset) |
| 523 | { |
| 524 | std::vector<float> inputData = { |
| 525 | -0.1f, -0.2f, -0.3f, -0.4f, |
| 526 | 0.1f, 0.2f, 0.3f, 0.4f, |
| 527 | -1.0f, -2.0f, -3.0f, -4.0f, |
| 528 | 1.0f, 2.0f, 3.0f, 4.0f |
| 529 | }; |
| 530 | |
| 531 | // Calculate output values for input. |
| 532 | auto f = [](float value) |
| 533 | { |
| 534 | return std::fmax(0.0f, value); |
| 535 | }; |
| 536 | std::vector<float> outputExpectedData(inputData.size()); |
| 537 | std::transform(inputData.begin(), inputData.end(), outputExpectedData.begin(), f); |
| 538 | |
| 539 | return SimpleActivationTest<ArmnnType>(workloadFactory, |
| 540 | memoryManager, |
| 541 | armnn::ActivationFunction::ReLu, |
| 542 | 0.f, |
| 543 | 0.f, |
| 544 | qScale, |
| 545 | qOffset, |
| 546 | inputData, |
Ferran Balaguer | b2b5a26 | 2019-06-24 12:43:38 +0100 | [diff] [blame] | 547 | qScale, |
| 548 | qOffset, |
Teresa Charlin | 18515e2 | 2019-04-24 10:17:46 +0100 | [diff] [blame] | 549 | outputExpectedData); |
| 550 | } |
| 551 | |
| 552 | LayerTestResult<int16_t, 4> ReLuInt16Test( |
| 553 | armnn::IWorkloadFactory& workloadFactory, |
| 554 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 555 | { |
| 556 | return ReLuTestCommon<armnn::DataType::QuantisedSymm16>(workloadFactory, memoryManager, 0.1f, 0); |
| 557 | } |
| 558 | |
| 559 | |
konsof01 | 7f6db40 | 2019-06-07 15:15:58 +0100 | [diff] [blame] | 560 | LayerTestResult<uint8_t, 4> ReLuUint8Test( |
| 561 | armnn::IWorkloadFactory& workloadFactory, |
| 562 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 563 | { |
| 564 | return ReLuTestCommon<armnn::DataType::QuantisedAsymm8>(workloadFactory, memoryManager, 0.1f, 0); |
| 565 | } |
| 566 | |
| 567 | LayerTestResult<float, 4> ReLuTest( |
| 568 | armnn::IWorkloadFactory& workloadFactory, |
| 569 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 570 | { |
| 571 | return ReLuTestCommon<armnn::DataType::Float32>(workloadFactory, memoryManager, 0.1f, 0); |
| 572 | } |
| 573 | |
| 574 | |
Teresa Charlin | 18515e2 | 2019-04-24 10:17:46 +0100 | [diff] [blame] | 575 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
| 576 | LayerTestResult<T, 4> BoundedReLuTestCommon( |
| 577 | armnn::IWorkloadFactory& workloadFactory, |
| 578 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 579 | float qScale, |
| 580 | int32_t qOffset) |
| 581 | { |
| 582 | std::vector<float> inputData = { |
| 583 | -0.1f, -0.2f, -0.3f, -0.4f, |
| 584 | 0.1f, 0.2f, 0.3f, 0.4f, |
| 585 | -1.0f, -2.0f, -3.0f, -4.0f, |
| 586 | 1.0f, 2.0f, 3.0f, 4.0f |
| 587 | }; |
| 588 | const float a = 1.0f; |
| 589 | const float b = -1.0f; |
| 590 | // Calculate output values for input. |
| 591 | auto f = [a, b](float value) |
| 592 | { |
| 593 | return std::min(a, std::max(b, value)); |
| 594 | }; |
| 595 | std::vector<float> outputExpectedData(inputData.size()); |
| 596 | std::transform(inputData.begin(), inputData.end(), outputExpectedData.begin(), f); |
| 597 | |
| 598 | return SimpleActivationTest<ArmnnType>(workloadFactory, |
| 599 | memoryManager, |
| 600 | armnn::ActivationFunction::BoundedReLu, |
| 601 | a, |
| 602 | b, |
| 603 | qScale, |
| 604 | qOffset, |
| 605 | inputData, |
Ferran Balaguer | b2b5a26 | 2019-06-24 12:43:38 +0100 | [diff] [blame] | 606 | qScale, |
| 607 | qOffset, |
Teresa Charlin | 18515e2 | 2019-04-24 10:17:46 +0100 | [diff] [blame] | 608 | outputExpectedData); |
| 609 | } |
| 610 | |
| 611 | LayerTestResult<int16_t, 4> BoundedReLuInt16Test( |
| 612 | armnn::IWorkloadFactory& workloadFactory, |
| 613 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 614 | { |
| 615 | return ReLuTestCommon<armnn::DataType::QuantisedSymm16>(workloadFactory, memoryManager, 0.1f, 0); |
| 616 | } |
| 617 | |
| 618 | |
| 619 | |
| 620 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
| 621 | LayerTestResult<T, 4> SoftReLuTestCommon( |
| 622 | armnn::IWorkloadFactory& workloadFactory, |
| 623 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 624 | float qScale, |
| 625 | int32_t qOffset) |
| 626 | { |
| 627 | std::vector<float> inputData = { |
| 628 | -0.1f, -0.2f, -0.3f, -0.4f, |
| 629 | 0.1f, 0.2f, 0.3f, 0.4f, |
| 630 | -1.0f, -2.0f, -3.0f, -4.0f, |
| 631 | 1.0f, 2.0f, 3.0f, 4.0f |
| 632 | }; |
| 633 | |
| 634 | // Calculate output values for input. |
| 635 | auto f = [](float value) |
| 636 | { |
| 637 | return std::log(1.0f + std::exp(value)); |
| 638 | }; |
| 639 | std::vector<float> outputExpectedData(inputData.size()); |
| 640 | std::transform(inputData.begin(), inputData.end(), outputExpectedData.begin(), f); |
| 641 | |
| 642 | return SimpleActivationTest<ArmnnType>(workloadFactory, |
| 643 | memoryManager, |
| 644 | armnn::ActivationFunction::SoftReLu, |
| 645 | 0.f, |
| 646 | 0.f, |
| 647 | qScale, |
| 648 | qOffset, |
| 649 | inputData, |
Ferran Balaguer | b2b5a26 | 2019-06-24 12:43:38 +0100 | [diff] [blame] | 650 | qScale, |
| 651 | qOffset, |
Teresa Charlin | 18515e2 | 2019-04-24 10:17:46 +0100 | [diff] [blame] | 652 | outputExpectedData); |
| 653 | } |
| 654 | |
konsof01 | 7f6db40 | 2019-06-07 15:15:58 +0100 | [diff] [blame] | 655 | LayerTestResult<float, 4> SoftReLuTest( |
| 656 | armnn::IWorkloadFactory& workloadFactory, |
| 657 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 658 | { |
| 659 | return SoftReLuTestCommon<armnn::DataType::Float32>(workloadFactory, memoryManager, 0.1f, 0); |
| 660 | } |
| 661 | |
| 662 | LayerTestResult<uint8_t, 4> SoftReLuUint8Test( |
| 663 | armnn::IWorkloadFactory& workloadFactory, |
| 664 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 665 | { |
| 666 | return SoftReLuTestCommon<armnn::DataType::QuantisedAsymm8>(workloadFactory, memoryManager, 0.0625f, 64); |
| 667 | } |
| 668 | |
Teresa Charlin | 18515e2 | 2019-04-24 10:17:46 +0100 | [diff] [blame] | 669 | LayerTestResult<int16_t, 4> SoftReLuInt16Test( |
| 670 | armnn::IWorkloadFactory& workloadFactory, |
| 671 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 672 | { |
| 673 | return SoftReLuTestCommon<armnn::DataType::QuantisedSymm16>(workloadFactory, memoryManager, 0.1f, 0); |
| 674 | } |
| 675 | |
| 676 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
| 677 | LayerTestResult<T, 4> LeakyReLuTestCommon( |
| 678 | armnn::IWorkloadFactory& workloadFactory, |
| 679 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 680 | float qScale, |
| 681 | int32_t qOffset) |
| 682 | { |
| 683 | std::vector<float> inputData = { |
| 684 | -0.1f, -0.2f, -0.3f, -0.4f, |
| 685 | 0.1f, 0.2f, 0.3f, 0.4f, |
| 686 | -1.0f, -2.0f, -3.0f, -4.0f, |
| 687 | 1.0f, 2.0f, 3.0f, 4.0f |
| 688 | }; |
| 689 | |
| 690 | const float a = 0.01f; |
| 691 | // Calculate output values for input. |
| 692 | auto f = [a](float value) |
| 693 | { |
| 694 | return value > 0.0f ? value : (value * a); |
| 695 | }; |
| 696 | std::vector<float> outputExpectedData(inputData.size()); |
| 697 | std::transform(inputData.begin(), inputData.end(), outputExpectedData.begin(), f); |
| 698 | |
| 699 | return SimpleActivationTest<ArmnnType>(workloadFactory, |
| 700 | memoryManager, |
| 701 | armnn::ActivationFunction::LeakyReLu, |
| 702 | a, |
| 703 | 0.f, |
| 704 | qScale, |
| 705 | qOffset, |
| 706 | inputData, |
Ferran Balaguer | b2b5a26 | 2019-06-24 12:43:38 +0100 | [diff] [blame] | 707 | qScale, |
| 708 | qOffset, |
Teresa Charlin | 18515e2 | 2019-04-24 10:17:46 +0100 | [diff] [blame] | 709 | outputExpectedData); |
| 710 | } |
| 711 | |
konsof01 | 7f6db40 | 2019-06-07 15:15:58 +0100 | [diff] [blame] | 712 | LayerTestResult<float, 4> LeakyReLuTest( |
| 713 | armnn::IWorkloadFactory& workloadFactory, |
| 714 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 715 | { |
| 716 | return LeakyReLuTestCommon<armnn::DataType::Float32>(workloadFactory, memoryManager, 0.1f, 0); |
| 717 | } |
| 718 | |
| 719 | LayerTestResult<uint8_t, 4> LeakyReLuUint8Test( |
| 720 | armnn::IWorkloadFactory& workloadFactory, |
| 721 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 722 | { |
| 723 | return LeakyReLuTestCommon<armnn::DataType::QuantisedAsymm8>(workloadFactory, memoryManager, 0.0625f, 64); |
| 724 | } |
| 725 | |
Teresa Charlin | 18515e2 | 2019-04-24 10:17:46 +0100 | [diff] [blame] | 726 | LayerTestResult<int16_t, 4> LeakyReLuInt16Test( |
| 727 | armnn::IWorkloadFactory& workloadFactory, |
| 728 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 729 | { |
| 730 | return LeakyReLuTestCommon<armnn::DataType::QuantisedSymm16>(workloadFactory, memoryManager, 0.1f, 0); |
| 731 | } |
| 732 | |
| 733 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
| 734 | LayerTestResult<T, 4> AbsTestCommon( |
| 735 | armnn::IWorkloadFactory& workloadFactory, |
| 736 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 737 | float qScale, |
| 738 | int32_t qOffset) |
| 739 | { |
| 740 | std::vector<float> inputData = { |
| 741 | -0.1f, -0.2f, -0.3f, -0.4f, |
| 742 | 0.1f, 0.2f, 0.3f, 0.4f, |
| 743 | -1.0f, -2.0f, -3.0f, -4.0f, |
| 744 | 1.0f, 2.0f, 3.0f, 4.0f |
| 745 | }; |
| 746 | |
| 747 | // Calculate output values for input. |
| 748 | auto f = [](float value) |
| 749 | { |
| 750 | return std::abs(value); |
| 751 | }; |
| 752 | std::vector<float> outputExpectedData(inputData.size()); |
| 753 | std::transform(inputData.begin(), inputData.end(), outputExpectedData.begin(), f); |
| 754 | |
| 755 | return SimpleActivationTest<ArmnnType>(workloadFactory, |
| 756 | memoryManager, |
| 757 | armnn::ActivationFunction::Abs, |
| 758 | 0.f, |
| 759 | 0.f, |
| 760 | qScale, |
| 761 | qOffset, |
| 762 | inputData, |
Ferran Balaguer | b2b5a26 | 2019-06-24 12:43:38 +0100 | [diff] [blame] | 763 | qScale, |
| 764 | qOffset, |
Teresa Charlin | 18515e2 | 2019-04-24 10:17:46 +0100 | [diff] [blame] | 765 | outputExpectedData); |
| 766 | } |
| 767 | |
konsof01 | 7f6db40 | 2019-06-07 15:15:58 +0100 | [diff] [blame] | 768 | LayerTestResult<float, 4> AbsTest( |
| 769 | armnn::IWorkloadFactory& workloadFactory, |
| 770 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 771 | { |
| 772 | return AbsTestCommon<armnn::DataType::Float32>(workloadFactory, memoryManager, 0.1f, 0); |
| 773 | } |
| 774 | |
| 775 | LayerTestResult<uint8_t, 4> AbsUint8Test( |
| 776 | armnn::IWorkloadFactory& workloadFactory, |
| 777 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 778 | { |
| 779 | return AbsTestCommon<armnn::DataType::QuantisedAsymm8>(workloadFactory, memoryManager, 0.0625f, 64); |
| 780 | } |
| 781 | |
Teresa Charlin | 18515e2 | 2019-04-24 10:17:46 +0100 | [diff] [blame] | 782 | LayerTestResult<int16_t, 4> AbsInt16Test( |
| 783 | armnn::IWorkloadFactory& workloadFactory, |
| 784 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 785 | { |
| 786 | return AbsTestCommon<armnn::DataType::QuantisedSymm16>(workloadFactory, memoryManager, 0.1f, 0); |
| 787 | } |
| 788 | |
Sadik Armagan | 6095ba5 | 2019-09-13 17:07:19 +0100 | [diff] [blame] | 789 | LayerTestResult<float, 5> SqrtNNTest( |
| 790 | armnn::IWorkloadFactory& workloadFactory, |
| 791 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 792 | { |
| 793 | const int inputDataSize = 120; |
| 794 | std::vector<float> inputData(inputDataSize); |
| 795 | |
| 796 | for (unsigned int i = 0u; i < inputDataSize; ++i) |
| 797 | { |
| 798 | inputData[i] = static_cast<float>(i) / 10; |
| 799 | } |
| 800 | |
| 801 | auto f = [](float value) |
| 802 | { |
| 803 | return std::sqrt(value); |
| 804 | }; |
| 805 | std::vector<float> outputExpectedData(inputDataSize); |
| 806 | std::transform(inputData.begin(), inputData.end(), outputExpectedData.begin(), f); |
| 807 | |
| 808 | armnn::TensorInfo inputTensorInfo( |
| 809 | { 1u, 2u, 3u, 4u, 5u }, armnn::DataType::Float32); |
| 810 | armnn::TensorInfo outputTensorInfo( |
| 811 | { 1u, 2u, 3u, 4u, 5u }, armnn::DataType::Float32); |
| 812 | |
| 813 | LayerTestResult<float, 5> result(inputTensorInfo); |
| 814 | |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 815 | auto input = MakeTensor<float, 5>(inputTensorInfo, inputData); |
Sadik Armagan | 6095ba5 | 2019-09-13 17:07:19 +0100 | [diff] [blame] | 816 | |
| 817 | std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo); |
| 818 | std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); |
| 819 | |
| 820 | armnn::ActivationQueueDescriptor descriptor; |
| 821 | armnn::WorkloadInfo workloadInfo; |
| 822 | AddInputToWorkload(descriptor, workloadInfo, inputTensorInfo, inputHandle.get()); |
| 823 | AddOutputToWorkload(descriptor, workloadInfo, outputTensorInfo, outputHandle.get()); |
| 824 | |
| 825 | descriptor.m_Parameters.m_Function = armnn::ActivationFunction::Sqrt; |
| 826 | |
| 827 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateActivation(descriptor, workloadInfo); |
| 828 | |
| 829 | inputHandle->Allocate(); |
| 830 | outputHandle->Allocate(); |
| 831 | |
| 832 | CopyDataToITensorHandle(inputHandle.get(), &input[0][0][0][0][0]); |
| 833 | |
| 834 | workload->Execute(); |
| 835 | |
| 836 | CopyDataFromITensorHandle(&result.output[0][0][0][0][0], outputHandle.get()); |
| 837 | |
| 838 | // Calculated manually. |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 839 | result.outputExpected = MakeTensor<float, 5>(outputTensorInfo, outputExpectedData); |
Sadik Armagan | 6095ba5 | 2019-09-13 17:07:19 +0100 | [diff] [blame] | 840 | |
| 841 | return result; |
| 842 | }; |
| 843 | |
Teresa Charlin | 18515e2 | 2019-04-24 10:17:46 +0100 | [diff] [blame] | 844 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
| 845 | LayerTestResult<T, 4> SqrtTestCommon( |
| 846 | armnn::IWorkloadFactory& workloadFactory, |
| 847 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 848 | float qScale, |
| 849 | int32_t qOffset) |
| 850 | { |
| 851 | std::vector<float> inputData = { |
| 852 | 0.1f, 0.2f, 0.3f, 0.4f, |
| 853 | 0.1f, 0.2f, 0.3f, 0.4f, |
| 854 | 1.0f, 2.0f, 3.0f, 4.0f, |
| 855 | 1.0f, 2.0f, 3.0f, 4.0f |
| 856 | }; |
| 857 | |
| 858 | // Calculate output values for input. |
| 859 | auto f = [](float value) |
| 860 | { |
| 861 | return std::sqrt(value); |
| 862 | }; |
| 863 | std::vector<float> outputExpectedData(inputData.size()); |
| 864 | std::transform(inputData.begin(), inputData.end(), outputExpectedData.begin(), f); |
| 865 | |
| 866 | return SimpleActivationTest<ArmnnType>(workloadFactory, |
| 867 | memoryManager, |
| 868 | armnn::ActivationFunction::Sqrt, |
| 869 | 0.f, |
| 870 | 0.f, |
| 871 | qScale, |
| 872 | qOffset, |
| 873 | inputData, |
Ferran Balaguer | b2b5a26 | 2019-06-24 12:43:38 +0100 | [diff] [blame] | 874 | qScale, |
| 875 | qOffset, |
Teresa Charlin | 18515e2 | 2019-04-24 10:17:46 +0100 | [diff] [blame] | 876 | outputExpectedData); |
| 877 | } |
| 878 | |
konsof01 | 7f6db40 | 2019-06-07 15:15:58 +0100 | [diff] [blame] | 879 | LayerTestResult<float, 4> SqrtTest( |
| 880 | armnn::IWorkloadFactory& workloadFactory, |
| 881 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 882 | { |
| 883 | return SqrtTestCommon<armnn::DataType::Float32>(workloadFactory, memoryManager, 0.1f, 0); |
| 884 | } |
| 885 | |
| 886 | LayerTestResult<uint8_t, 4> SqrtUint8Test( |
| 887 | armnn::IWorkloadFactory& workloadFactory, |
| 888 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 889 | { |
| 890 | return SqrtTestCommon<armnn::DataType::QuantisedAsymm8>(workloadFactory, memoryManager, 0.0625f, 64); |
| 891 | } |
| 892 | |
Teresa Charlin | 18515e2 | 2019-04-24 10:17:46 +0100 | [diff] [blame] | 893 | LayerTestResult<int16_t, 4> SqrtInt16Test( |
| 894 | armnn::IWorkloadFactory& workloadFactory, |
| 895 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 896 | { |
| 897 | return SqrtTestCommon<armnn::DataType::QuantisedSymm16>(workloadFactory, memoryManager, 0.1f, 0); |
| 898 | } |
| 899 | |
| 900 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
| 901 | LayerTestResult<T, 4> SquareTestCommon( |
| 902 | armnn::IWorkloadFactory& workloadFactory, |
| 903 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 904 | float qScale, |
| 905 | int32_t qOffset) |
| 906 | { |
| 907 | std::vector<float> inputData = { |
| 908 | -0.1f, -0.2f, -0.3f, -0.4f, |
| 909 | 0.1f, 0.2f, 0.3f, 0.4f, |
| 910 | -1.0f, -2.0f, -3.0f, -4.0f, |
| 911 | 1.0f, 2.0f, 3.0f, 4.0f |
| 912 | }; |
| 913 | |
| 914 | // Calculate output values for input. |
| 915 | auto f = [](float value) |
| 916 | { |
| 917 | return std::pow(value,2); |
| 918 | }; |
| 919 | std::vector<float> outputExpectedData(inputData.size()); |
| 920 | std::transform(inputData.begin(), inputData.end(), outputExpectedData.begin(), f); |
| 921 | |
| 922 | return SimpleActivationTest<ArmnnType>(workloadFactory, |
| 923 | memoryManager, |
| 924 | armnn::ActivationFunction::Square, |
| 925 | 0.f, |
| 926 | 0.f, |
| 927 | qScale, |
| 928 | qOffset, |
| 929 | inputData, |
Ferran Balaguer | b2b5a26 | 2019-06-24 12:43:38 +0100 | [diff] [blame] | 930 | qScale, |
| 931 | qOffset, |
Teresa Charlin | 18515e2 | 2019-04-24 10:17:46 +0100 | [diff] [blame] | 932 | outputExpectedData); |
| 933 | } |
| 934 | |
konsof01 | 7f6db40 | 2019-06-07 15:15:58 +0100 | [diff] [blame] | 935 | LayerTestResult<float, 4> SquareTest( |
| 936 | armnn::IWorkloadFactory& workloadFactory, |
| 937 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 938 | { |
| 939 | return SquareTestCommon<armnn::DataType::Float32>(workloadFactory, memoryManager, 0.1f, 0); |
| 940 | } |
| 941 | |
| 942 | LayerTestResult<uint8_t, 4> SquareUint8Test( |
| 943 | armnn::IWorkloadFactory& workloadFactory, |
| 944 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 945 | { |
| 946 | return SquareTestCommon<armnn::DataType::QuantisedAsymm8>(workloadFactory, memoryManager, 0.0625f, 64); |
| 947 | } |
| 948 | |
Teresa Charlin | 18515e2 | 2019-04-24 10:17:46 +0100 | [diff] [blame] | 949 | LayerTestResult<int16_t, 4> SquareInt16Test( |
| 950 | armnn::IWorkloadFactory& workloadFactory, |
| 951 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 952 | { |
| 953 | return SquareTestCommon<armnn::DataType::QuantisedSymm16>(workloadFactory, memoryManager, 0.1f, 0); |
| 954 | } |
| 955 | |
| 956 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
| 957 | LayerTestResult<T, 4> TanhTestCommon( |
| 958 | armnn::IWorkloadFactory& workloadFactory, |
| 959 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 960 | float qScale, |
| 961 | int32_t qOffset) |
| 962 | { |
| 963 | std::vector<float> inputData = { |
| 964 | -0.1f, -0.2f, -0.3f, -0.4f, |
| 965 | 0.1f, 0.2f, 0.3f, 0.4f, |
| 966 | -1.0f, -2.0f, -3.0f, -4.0f, |
| 967 | 1.0f, 2.0f, 3.0f, 4.0f |
| 968 | }; |
| 969 | |
| 970 | const float a = 2.0f; |
| 971 | const float b = 3.0f; |
| 972 | // Calculate output values for input. |
| 973 | auto f = [a, b](float value) |
| 974 | { |
| 975 | return a * tanhf(b * value); |
| 976 | }; |
| 977 | std::vector<float> outputExpectedData(inputData.size()); |
| 978 | std::transform(inputData.begin(), inputData.end(), outputExpectedData.begin(), f); |
| 979 | |
| 980 | return SimpleActivationTest<ArmnnType>(workloadFactory, |
| 981 | memoryManager, |
| 982 | armnn::ActivationFunction::TanH, |
| 983 | a, |
| 984 | b, |
| 985 | qScale, |
| 986 | qOffset, |
| 987 | inputData, |
Ferran Balaguer | b2b5a26 | 2019-06-24 12:43:38 +0100 | [diff] [blame] | 988 | qScale, |
| 989 | qOffset, |
Teresa Charlin | 18515e2 | 2019-04-24 10:17:46 +0100 | [diff] [blame] | 990 | outputExpectedData); |
| 991 | } |
| 992 | |
konsof01 | 7f6db40 | 2019-06-07 15:15:58 +0100 | [diff] [blame] | 993 | LayerTestResult<float, 4> TanhTest( |
| 994 | armnn::IWorkloadFactory& workloadFactory, |
| 995 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 996 | { |
| 997 | return TanhTestCommon<armnn::DataType::Float32>(workloadFactory, memoryManager, 0.1f, 0); |
| 998 | } |
| 999 | |
| 1000 | LayerTestResult<uint8_t, 4> TanhUint8Test( |
| 1001 | armnn::IWorkloadFactory& workloadFactory, |
| 1002 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 1003 | { |
| 1004 | return TanhTestCommon<armnn::DataType::QuantisedAsymm8>(workloadFactory, memoryManager, 0.1f, 64); |
| 1005 | } |
| 1006 | |
Teresa Charlin | 18515e2 | 2019-04-24 10:17:46 +0100 | [diff] [blame] | 1007 | LayerTestResult<int16_t, 4> TanhInt16Test( |
| 1008 | armnn::IWorkloadFactory& workloadFactory, |
| 1009 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 1010 | { |
| 1011 | return TanhTestCommon<armnn::DataType::QuantisedSymm16>(workloadFactory, memoryManager, 0.1f, 0); |
| 1012 | } |
| 1013 | |
| 1014 | |
| 1015 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 1016 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 1017 | LayerTestResult<T,4> CompareActivationTestImpl( |
| 1018 | armnn::IWorkloadFactory& workloadFactory, |
| 1019 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 1020 | armnn::IWorkloadFactory& refWorkloadFactory, |
| 1021 | armnn::ActivationFunction f, |
| 1022 | unsigned int batchSize = 5, |
| 1023 | float qScale = 0.0f, |
| 1024 | int32_t qOffset = 0) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1025 | { |
| 1026 | unsigned int width = 17; |
| 1027 | unsigned int height = 29; |
| 1028 | unsigned int channels = 2; |
| 1029 | |
| 1030 | float a = 0.234f; |
| 1031 | float b = -12.345f; |
| 1032 | |
| 1033 | armnn::TensorInfo inputTensorInfo; |
| 1034 | armnn::TensorInfo outputTensorInfo; |
| 1035 | |
| 1036 | unsigned int shape[] = {batchSize, channels, height, width}; |
| 1037 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 1038 | inputTensorInfo = armnn::TensorInfo(4, shape, ArmnnType); |
| 1039 | outputTensorInfo = armnn::TensorInfo(4, shape, ArmnnType); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1040 | |
| 1041 | // Set quantization parameters if the requested type is a quantized type. |
| 1042 | if(armnn::IsQuantizedType<T>()) |
| 1043 | { |
| 1044 | inputTensorInfo.SetQuantizationScale(qScale); |
| 1045 | inputTensorInfo.SetQuantizationOffset(qOffset); |
| 1046 | outputTensorInfo.SetQuantizationScale(qScale); |
| 1047 | outputTensorInfo.SetQuantizationOffset(qOffset); |
| 1048 | } |
| 1049 | |
| 1050 | float minVal = -10.f; |
| 1051 | if (f == armnn::ActivationFunction::Sqrt) |
| 1052 | { |
| 1053 | minVal = 0.f; |
| 1054 | } |
| 1055 | |
| 1056 | boost::multi_array<T, 4> input = MakeRandomTensor<T, 4>(inputTensorInfo, 21453, minVal, 10.f); |
| 1057 | |
| 1058 | |
| 1059 | LayerTestResult<T,4> ret(outputTensorInfo); |
| 1060 | auto boostArrayExtents = boost::extents |
| 1061 | [boost::numeric_cast<boost::multi_array_types::extent_gen::index>(batchSize)] |
| 1062 | [boost::numeric_cast<boost::multi_array_types::extent_gen::index>(channels)] |
| 1063 | [boost::numeric_cast<boost::multi_array_types::extent_gen::index>(height)] |
| 1064 | [boost::numeric_cast<boost::multi_array_types::extent_gen::index>(width)]; |
| 1065 | ret.output.resize(boostArrayExtents); |
| 1066 | ret.outputExpected.resize(boostArrayExtents); |
| 1067 | |
| 1068 | |
| 1069 | std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo); |
| 1070 | std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); |
| 1071 | |
| 1072 | std::unique_ptr<armnn::ITensorHandle> inputHandleRef = refWorkloadFactory.CreateTensorHandle(inputTensorInfo); |
| 1073 | std::unique_ptr<armnn::ITensorHandle> outputHandleRef = refWorkloadFactory.CreateTensorHandle(outputTensorInfo); |
| 1074 | |
| 1075 | armnn::ActivationQueueDescriptor data; |
| 1076 | armnn::WorkloadInfo info; |
| 1077 | AddInputToWorkload(data, info, inputTensorInfo, inputHandle.get()); |
| 1078 | AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get()); |
| 1079 | data.m_Parameters.m_A = a; |
| 1080 | data.m_Parameters.m_B = b; |
| 1081 | data.m_Parameters.m_Function = f; |
| 1082 | |
| 1083 | armnn::ActivationQueueDescriptor refData = data; |
| 1084 | armnn::WorkloadInfo refInfo = info; |
| 1085 | SetWorkloadInput(refData, refInfo, 0, inputTensorInfo, inputHandleRef.get()); |
| 1086 | SetWorkloadOutput(refData, refInfo, 0, outputTensorInfo, outputHandleRef.get()); |
| 1087 | |
| 1088 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateActivation(data, info); |
| 1089 | BOOST_ASSERT(workload != nullptr); |
| 1090 | std::unique_ptr<armnn::IWorkload> workloadRef = refWorkloadFactory.CreateActivation(refData, refInfo); |
| 1091 | BOOST_ASSERT(workloadRef != nullptr); |
| 1092 | |
| 1093 | inputHandle->Allocate(); |
| 1094 | outputHandle->Allocate(); |
| 1095 | inputHandleRef->Allocate(); |
| 1096 | outputHandleRef->Allocate(); |
| 1097 | |
| 1098 | CopyDataToITensorHandle(inputHandle.get(), &input[0][0][0][0]); |
| 1099 | CopyDataToITensorHandle(inputHandleRef.get(), &input[0][0][0][0]); |
| 1100 | |
| 1101 | workload->Execute(); |
| 1102 | workloadRef->Execute(); |
| 1103 | |
| 1104 | CopyDataFromITensorHandle(&ret.output[0][0][0][0], outputHandle.get()); |
| 1105 | CopyDataFromITensorHandle(&ret.outputExpected[0][0][0][0], outputHandleRef.get()); |
| 1106 | |
| 1107 | return ret; |
| 1108 | } |
| 1109 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 1110 | LayerTestResult<float,4> CompareActivationTest( |
| 1111 | armnn::IWorkloadFactory& workloadFactory, |
| 1112 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 1113 | armnn::IWorkloadFactory& refWorkloadFactory, |
| 1114 | armnn::ActivationFunction f, |
| 1115 | unsigned int batchSize) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1116 | { |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 1117 | return CompareActivationTestImpl<armnn::DataType::Float32>( |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 1118 | workloadFactory, memoryManager, refWorkloadFactory, f, batchSize); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1119 | } |
| 1120 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 1121 | LayerTestResult<uint8_t,4> CompareActivationUint8Test( |
| 1122 | armnn::IWorkloadFactory& workloadFactory, |
| 1123 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 1124 | armnn::IWorkloadFactory& refWorkloadFactory, |
| 1125 | armnn::ActivationFunction f) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1126 | { |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 1127 | return CompareActivationTestImpl<armnn::DataType::QuantisedAsymm8>( |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 1128 | workloadFactory, memoryManager, refWorkloadFactory, f, 5, 0.1f, 50); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1129 | } |
Teresa Charlin | 18515e2 | 2019-04-24 10:17:46 +0100 | [diff] [blame] | 1130 | |
| 1131 | LayerTestResult<int16_t,4> CompareActivationInt16Test( |
| 1132 | armnn::IWorkloadFactory& workloadFactory, |
| 1133 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 1134 | armnn::IWorkloadFactory& refWorkloadFactory, |
| 1135 | armnn::ActivationFunction f) |
| 1136 | { |
| 1137 | return CompareActivationTestImpl<armnn::DataType::QuantisedSymm16>( |
| 1138 | workloadFactory, memoryManager, refWorkloadFactory, f, 5, 0.1f, 0); |
| 1139 | } |